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Defence Research and Development Canada Scientific Report

DRDC-RDDC-2019-R106

February 2020

CAN UNCLASSIFIED

CAN UNCLASSIFIED

Use of small unmanned underwater vehicles for environmental battlespace characterization in support of naval mine countermeasures

Anna Crawford DRDC – Atlantic Research Centre

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IMPORTANT INFORMATIVE STATEMENTS

This document was reviewed for Controlled Goods by Defence Research and Development Canada (DRDC) using the Schedule to the Defence Production Act.

Disclaimer: This publication was prepared by Defence Research and Development Canada an agency of the Department of National Defence. The information contained in this publication has been derived and determined through best practice and adherence to the highest standards of responsible conduct of scientific research. This information is intended for the use of the Department of National Defence, the Canadian Armed Forces (“Canada”) and Public Safety partners and, as permitted, may be shared with academia, industry, Canada’s allies, and the public (“Third Parties”). Any use by, or any reliance on or decisions made based on this publication by Third Parties, are done at their own risk and responsibility. Canada does not assume any liability for any damages or losses which may arise from any use of, or reliance on, the publication.

Endorsement statement: This publication has been peer-reviewed and published by the Editorial Office of Defence Research and Development Canada, an agency of the Department of National Defence of Canada. Inquiries can be sent to: [email protected].

© Sa Majesté la Reine en droit du Canada (Ministère de la Défense nationale), 2020

© Her Majesty the Queen in Right of Canada (Department of National Defence), 2020

DRDC-RDDC-2019-R106 i

Abstract

Defence Research and Development Canada (DRDC) has participated with international (The Technical Cooperation Program (TTCP)) partners in pre-trial environmental characterization exercises prior to three out of four of the Hell Bay trials. In each case, environmental data was collected using small Unmanned Underwater Vehicles (UUVs), as well as other sensors, and compiled into a comprehensive data package that was delivered to follow-on Mine Countermeasures (MCM) exercise participants, to improve odds of success in planned missions. The experience gained in the planning and execution of these substantial pre-trial survey exercises and in collaboration on development of useful environmental data products, was invaluable and serves as an example of the benefits of international cooperation. It is an accepted fact that knowledge of the operational environment is key to success.

This Scientific Report presents an overview of environmental parameters relevant to follow-on MCM seabed survey operations and potential effects of environmental factors, summarizes current small UUV technology and sensors for making environmental measurements, presents examples of environmental data products that were included in the compiled data packages and a summary of lessons learned.

Significance to defence and security

The Royal Canadian Navy (RCN) has very recently taken delivery of small UUVs at the Fleet Diving Units (FDUs) on both coasts, intended for the purposes of routine and contingency area searches, seabed imaging, water column investigation, and also including under-ice operations. These are specifically not MCM assets. This is an opportunity for DRDC to provide timely and topical advice on collection of environmental data using UUVs, on the potential benefits and best practices, and to gather feedback on what is useful operationally, to maintain the relevance of the DRDC research program.

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Résumé

RDDC a pris part avec des partenaires internationaux (TTCP) à des exercices de caractérisation environnementale préalables aux essais avant trois des quatre essais menés à Hell Bay. Dans chaque cas, les données environnementales ont été recueillies au moyen de petits véhicules sous-marins sans équipages (VSSE) ainsi que d’autres capteurs, lesquels ont permis la compilation d’un ensemble de données complet livré aux participants à l’exercice de LCM suivant afin d’améliorer les chances de succès lors des missions planifiées. L’expérience acquise durant la planification et l’exécution de ces exercices de levé préalables aux essais, ainsi que lors de la collaboration aux fins de l’élaboration de produits de données environnementales utiles, a été extrêmement précieuse et sert d’exemple des avantages que l’on peut tirer de la coopération internationale. Il est reconnu que la connaissance de l’environnement opérationnel est un élément clé du succès.

Le présent rapport donne un aperçu des paramètres environnementaux pertinents pour les opérations de levé des fonds marins dans le cadre de la LCM, ainsi que des effets potentiels des facteurs environnementaux; il dresse un sommaire de l’état de la technologie actuelle des VSSE et des capteurs qui servent à prendre des mesures environnementales, il offre des exemples de produits de données environnementales inclus dans les ensembles de données compilés de même qu’un sommaire des leçons apprises.

Importance pour la défense et la sécurité

La MRC a très récemment pris livraison de petits VSSE dans les Unités de plongée de la flotte des deux côtes, et elle prévoit s’en servir pour mener des recherches sur zone de routine et d’urgence, saisir de l’imagerie des fonds marins, examiner des colonnes d’eau et tenir des opérations sous la glace. Ce ne sont pas des ressources qui sont propres à la LCM. Il s’agit là d’une occasion pour RDDC de fournir en temps opportun des conseils thématiques sur la collecte de données environnementales au moyens de VSSE, ainsi que sur les avantages potentiels et les pratiques exemplaires liés à de telles activités, et de recueillir de la rétroaction sur ce qui est opérationnellement utile afin de maintenir la pertinence du programme de recherche de RDDC.

DRDC-RDDC-2019-R106 iii

Table of contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Significance to defence and security . . . . . . . . . . . . . . . . . . . . . . . . . i

Résumé . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii

Importance pour la défense et la sécurité . . . . . . . . . . . . . . . . . . . . . . . ii

Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

List of figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

List of tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2 Review of relevant environmental parameters . . . . . . . . . . . . . . . . . . . . 3

3 Aspects of NMCM UUV operations which can be impacted by environmental effects . . . . . 6

4 Small UUVs and sensor fits for environmental measurements . . . . . . . . . . . . . 10

5 Examples of environmental data products collected using small UUVs . . . . . . . . . . 13

5.1 Bathymetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

5.2 Currents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

5.3 Water properties—temperature, salinity and other . . . . . . . . . . . . . . . 19

5.4 Bottom cover, clutter . . . . . . . . . . . . . . . . . . . . . . . . . . 20

5.5 Obstacles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

5.6 Magnetic anomaly . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

6 Use of autonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

7 Software and training considerations . . . . . . . . . . . . . . . . . . . . . . 26

8 Manning and tempo considerations . . . . . . . . . . . . . . . . . . . . . . . 29

9 Conclusion and recommendations . . . . . . . . . . . . . . . . . . . . . . . 31

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Annex A Table of environmental parameters prepared during planning for Hell Bay 4 . . . . . 35

Annex B Summary report on observed currents during Hell Bay 4 . . . . . . . . . . . . 37

List of symbols/abbreviations/acronyms/initialisms . . . . . . . . . . . . . . . . . . 39

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List of figures

Figure 1: Planning UUV missions and PMA at Hell Bay 4 (photos: Cmdr. S. Carrizosa). . . . . 5

Figure 2: Example of sidescan sonar data negatively affected by environmental conditions. . . . 7

Figure 3: Recovering an Iver2 in Loch Alsh, Hell Bay 4 (photo: Cmdr. S. Carrizosa). . . . . . 9

Figure 4: Small UUVs at the Hell Bay 4 trial. (left) 4 Iver3 UUVs being prepared for an environmental survey (photo: Cmdr. S. Carrizosa). (right) 3 Iver3 and 4 REMUS 100 UUVs at the UMS KTA MCM trial (photo: UMS KTA). . . . . . . . . . . . . 10

Figure 5: Range craft (Quasar) and two 8-m RHIBs used during Hell Bay 4 (photo: Cmdr. S. Carrizosa). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 6: Comparison of bathymetry data collected off San Diego using 3 Iver UUVs with different sonar systems (Klein, Edgetech and Imagenex Delta-T) during Hell Bay 1. Chart depths are in fathoms. . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 7: Currents measured by UUV (green arrows) plotted on top of vehicle track (blue line), overlaid on a chart. A scale arrow for the currents is difficult to see, drawn across the top of the rectangular mission area. . . . . . . . . . . . . . . . . . . . . . . . . 15

Figure 8: Screen shot of a current profile spreadsheet prepared from UUV-measured current data during Hell Bay 4. . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Figure 9: UUV-measured current profiles (downward- and upward-looking) in the Patuxent River estuary, Hell Bay 3. The heavier black line is the vehicle vertical position along the track and lighter black line is water depth. . . . . . . . . . . . . . . . . 18

Figure 10: Water properties (left to right, temperature, salinity and dissolved oxygen) sampled by UUV while underway on a long ingress mission during Hell Bay 4. Colour-coded values are plotted along the vehicle mission track. . . . . . . . . . . . . . . . 20

Figure 11: Results of PMA of sidescan sonar data collected in Hell Bay 4 to determine clutter density in a sub-section of the Op Area (graphic prepared by US FST). . . . . . . 21

Figure 12: No-Go area containing a high concentration of fishing gear, mapped using a UUV (graphic prepared by US FST). . . . . . . . . . . . . . . . . . . . . . . 22

Figure 13: Contoured magnetic anomaly data (white lines) overlaid on a sidescan image mosaic. The locations of the East-West UUV mission tracks are shown by the blue arrows (graphic prepared by HYPACK, Hell Bay 1). . . . . . . . . . . . . . . . . 23

Figure 14: Chart showing tracks of two UUVs executing contour-following behaviour during Hell Bay 4. The green line follows 20 m water depth and the brown line follows 5 m. . . 25

DRDC-RDDC-2019-R106 v

List of tables

Table 1: Environmental parameters of importance to sidescan sonar NMCM operations. . . . . 3

Table 2: Software used in preparation of data products shown in this report. . . . . . . . . 26

Table 3: Time requirements for tasks in production of the data product shown in Figure 11. . 29

Table A.1: Environmental parameters affecting performance of MCM assets operating in littoral waters for each phase of MCM operations and change detection. Only in-water and seabed parameters are included: meteorological parameters are listed in a separate table. . . . . 36

Table A.2: Meteorological and atmospheric environmental parameters affecting MCM operations. 36

Table A.3: Environmental factors affecting MCM diving operations. . . . . . . . . . . . . 36

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Acknowledgements

It takes a large team to stage any international trial and this would not have been possible without the TTCP partners. Listed here are the participants in the environmental characterization parts of these trials, coordinated by the Battlespace Characterization (BC) Key Technical Area (KTA) of Technical Panel (TP-13). These were smaller subsets of the national presences than the larger Unmanned Systems KTA exercises that followed in all three instances. The trial lead for all three BC KTA efforts was Mike Incze (United States of America (US), Naval Undersea Warfare Center (NUWC)). Some figures appearing in this report were prepared by the international (US and UK) collaborators, and these are used with permission. Chart imagery (Figures 7, 10, 11, 12, 14 and in Annex B) reproduced with permission from the UKHO. Crown copyright © 2020. Figure 6 includes chart imagery provided by NOAA Office of Coast Survey, nauticalcharts.noaa.gov.

Hell Bay 1: · US: Mike Incze, Scott Sideleau (NUWC)

Rick Allard (Naval Reseach Laboratory (NRL) Stennis Space Center (SSC), BC KTA Lead)

· UK: Tim Clarke, Calum Meredith (Defence Science and Technology Laboratory (dstl))

· CAN: Anna Crawford (DRDC)

· OEM (Original Equipment Manufacturer) Support: L3 OceanServer: Jason Aiello, Mike Ferreira

Klein Marine Systems: Straud Armstrong, Yuhui Ai

Edgetech: Gary Kozak, Rick Babicz, Damon Wolfe

Marine Magnetics: Melissa Marlowe

HYPACK: Harold Olinsky

SeeByte: Rob Cornick, Scott Reed, Alastair Cormack, Jon Wood

· SPAWAR (Space and Naval Warfare Command): Steve Koepenick, Dan Kichura, Mike Stuckenschneider, Lonnie Hamme, Tim Rainer, Martin Stacy, many others on site

Hell Bay 3: · US: Mike Incze, Scott Sideleau (NUWC)

Rick Allard (BC KTA Lead), Todd Holland (NRL SSC)

US Navy Naval Oceanography Mine Warfare Center (NOMWC)

US Navy Naval Oceanography Special Warfare Center (NOSWC)

· UK: Tim Clarke, Calum Meredith (dstl)


· OEM Support: L3 OceanServer: Daryl Slocum

· Naval Air Station (NAS) Pax River: Robert Gibson, Brian Wallace, Randy Brown, many others on site

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Hell Bay 4: · US: Mike Incze, Chris Gagner (NUWC)

Rick Allard (BC KTA Lead), Todd Holland (NRL SSC)

Brett Martin (NRL)

Commander Santiago Carrizosa (ONR-RC, US GEOINT liaison)

US Navy Fleet Survey Team (FST)

US Navy NOSWC

US Navy Explosive Ordnance Disposal Mobile Unit 8 (EODMU8)

· UK: Tim Clarke, Calum Meredith (dstl)


· OEM Support: L3 OceanServer: Daryl Slocum

· BUTEC (QinetiQ): Steve Wilkinson, many others on site

At DRDC, the technical support trials team maintains equipment, stages work-ups, arranges shipping, provides software and logistical support, and much more. This team included: Al Tremblay, Jason Murphy, Tim Murphy, Owen Shuttleworth and Brett Pickrill.

This document was improved greatly in response to comments from an anonymous DRDC reviewer.

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DRDC-RDDC-2019-R106 1

1 Introduction

It is widely accepted that knowledge of the operating environment is critical to mission success in almost all operational scenarios. In the case of Naval Mine Countermeasures (NMCM) operations, the environment directly affects sensor (in this case, sidescan sonar) performance and must be considered in the planning of missions in order to achieve coverage or clearance mission objectives. When small Unmanned Underwater Vehicles (UUVs) are used for NMCM survey, prior knowledge of the operating environment is particularly critical as autonomous behaviours allowing on-the-fly mission replanning have not yet reached maturity. Factors as basic as water depth across a littoral operating area, currents or water density, can have critical impact on mission success.

The Mine Warfare research group at DRDC – Atlantic Research Centre is currently in the first half of a multi-year program titled Emerging Techniques in NMCM (01cf). In the recent past, the program has leveraged international participation in several The Technical Cooperation Program (TTCP) Key Technical Areas (KTAs)—Unmanned Systems (UMS), Battlespace Characterization (BC), Ship-Mine Interaction (SMI) and Sensors—to achieve project objectives and to take part in larger scale collaborative trials that would not be feasible for Canada alone. The current NMCM project follows on from the former project (01cb) which benefited from participation in the Hell Bay series of trials led by the UMS KTA. The BC KTA has held pre-trial environmental characterization exercises prior to several of these trials: Hell Bay 1 (San Diego, 2013) [1], Hell Bay 3 (Naval Air Station Patuxent River, 2015) [2] and Hell Bay 4 (part of the Unmanned Warrior 2016 Exercise, Loch Alsh, Scotland) [3].

Broadly stated, the main objective of the Hell Bay environmental characterization exercises was to demonstrate collection of a comprehensive environmental data set which was then to be provided to MCM planners preparing missions for autonomous vehicles participating in the follow-on UMS trial serials—a function referred to as Intelligence Preparation of the Operational Environment (IPOE). Secondary objectives included investigation of how best to assess the benefits of having environmental data available during later mission planning, assessment of UUV-collected survey data quality, and comparison between measured and modelled data products to assess utility of environmental model output. These exercises were led by a US member of the KTA (Mike Incze, NUWC, now BC KTA Lead), with direct participation by other US, United Kingdom (UK) and Canadian KTA members. Environmental data were collected using a variety of sensors and platforms, including UUVs, wave drifter buoys, bottom deployed current profilers, tide gauges, meteorological sensors, etc., along with simultaneous model output of tides and currents. All data products were uploaded to a password protected web accessible repository hosted by NRL (US), to be available to the follow-on MCM exercise mission planners.

The experience gained in participating in and observing these large multi-national exercises is invaluable. In Canada’s case, UUVs are only very recently in operational service within the Canadian Armed Forces (CAF). Participation in the Hell Bay series has provided first-hand exposure and insight into operational considerations, Concept of Operations (CONOPs) and Standard Operating Procedures (SOPs), as well as manning and training requirements, for effective UUV usage in a NMCM context. This adds to the already considerable experience with UUV operations that DRDC has in-house, gained through the preceding years of the MCM research program.

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The Director General Naval Force Development’s Concept for Maritime Unmanned Systems (MUS) opens by stating “The RCN will acquire, integrate and exploit unmanned systems to both enhance existing maritime capabilities and potentially provide new ones.” [4] UUVs offer the capability of providing situational awareness of an operating area through unmanned, off board, and covert means.

The RCN has very recently (late 2018) taken delivery of small UUVs through a program called the Shallow Seabed Intervention Autonomous Underwater Vehicle (SSI AUV) Program. This program has delivered REMUS 100 UUVs to the FDUs on both coasts, for the purposes of routine and contingency area searches, seabed imaging, water column investigation, and also including under-ice operations. This is an opportunity for DRDC to provide timely and relevant advice on collection of environmental data using UUVs, on the potential benefits and best practices, and to gather feedback on what is useful operationally, to maintain the relevance of the DRDC research program.

The purpose of this Scientific Report is to summarize the experiences and lessons learned through participation in the environmental characterization phases of the Hell Bay series of trials, where small UUVs were used to collect environmental data specifically to aid planning in the follow-on MCM exercises. More emphasis will be placed on the last Hell Bay trial, the fourth, as lessons learned from the earlier trials were folded into its execution with incremental improvements.


2 Review of relevant environmental parameters

As part of the preparations for Hell Bay 4, a table of environmental parameters relevant to NMCM operations was prepared and circulated among the participating BC KTA nations (US, CA, UK), with a request for feedback particularly from operational personnel [1]. This table and the comments received provided a framework for planning of the environmental surveys in an exercise called SMRT (Support of MCM through Rapid Environmental Assessment—Tactical), performed prior to the UMS KTA serials in the Hell Bay 4 trial [3]. This table is included here in Annex A. Environmental data representing a subset of these parameters was collected during SMRT, and products were processed and distributed to the UMS KTA, as well as to participants of the MCM segment of the larger Unmanned Warrior 2016 exercise.

The set of parameters prepared prior to Hell Bay 4 (in Annex A) is extensive and very generalized. Presented in Table 1 is a reorganized and resampled list that includes the variables that survey operations conducted using small UUVs can typically provide. It is presumed that the survey sensor in use for follow-on minehunting is sidescan sonar, either towed or UUV fit, so the parameters listed in Table 1 are those that impact sensor performance and navigation, and for UUVs equipped with underwater modems, acoustic communications. The prior environmental survey may or may not include seabed survey, depending on the sensor fit of the UUV assets used and the objectives.

Table 1: Environmental parameters of importance to sidescan sonar NMCM operations.

Parameter UUV sensor(s) used for measurement

Relevance to follow-on sidescan survey mission

Water depth (including tide)

Interferometric sidescan sonar Multi-beam sonar Altimeter & pressure sensor Doppler Velocity Log (DVL)

Altitude for optimal sidescan sonar imaging performance imposes a minimum water depth.

Safety of navigation in shallow water.

Variable water depth across operations area complicates cable handling for towed systems and towed systems need more room to execute turns.

Range performance of sidescan sonar and acoustic communications is generally poorer in very shallow water.

Seabed slope Interferometric sidescan Multi-beam sonar Altimeter & pressure sensor DVL

Altitude keeping is slope-limited to maintain optimal sidescan sonar geometry and for obstacle/seabed avoidance.

Sidescan sonar image quality degrades looking up or down steep slopes.




Water temperature (T), salinity (S), Sound Velocity Profile (SVP)

Conductivity-Temperature-Depth (CTD) sensor Sonde

T and S affect UUV buoyancy (ballasting).

SVP affects sidescan sonar and acoustic communications range performance via refraction.

Currents DVL/Acoustic Doppler Current Profiler (ADCP)

Navigation precision affected by limited ability to counter currents by UUVs, towed systems pushed off track by cross currents.

Sidescan sonar image quality affected by crabbing and yaw motion across currents.

Waves, surf, swell DVL/ADCP Inertial Measurement Unit (IMU) (pitch, roll, yaw, heave sensor)

Sidescan sonar image quality degraded by sonar pitch/roll/yaw/heave motions.

Navigation performance degraded.

Bubble plumes from surf or whitecapping block sonar signals.

Obstacles, obstructions, flotsam

Sidescan sonar Interferometric sidescan sonar Multi-beam sonar Camera

Collision, entanglement, sensor fouling.

Bottom type, cover, clutter, ripples

Sidescan sonar Multi-beam sonar Camera

Minehunting difficulty increases in complex bottom types and clutter.

Bottom composition

Sidescan sonar Multi-beam sonar Sub-bottom profiler (acoustic) Camera

Relates to probability of mine burial and seabed complexity.

Magnetic anomaly Magnetometer Provides target identification information (magnetic vs. non-magnetic) or for buried object detection.

Other possible UUV sensor products: Optical properties (illumination, turbidity, water clarity)

Sonde Camera

Visibility for camera, or follow-on diver/Remotely Operated Vehicle (ROV) clearance operations.




Other water properties, such as dissolved oxygen, chlorophyll, pH, etc.

Sonde Water quality for follow-on diver operations.

As the set of variables in Table 1 is specific to data that can be collected using UUVs, not included are large scale external factors such as weather conditions and vessel traffic, which clearly could severely impact operations particularly for small boats, but are not within the scope of this discussion. The variables listed can be reasonably addressed using UUV assets with sensor fits that are available from commercial suppliers at this time.

It should be pointed out that some of the environmental water properties included in the list are measured from the water that the UUV onboard sensors pass through (e.g., salinity, temperature, optical properties), while others are remotely sensed (e.g., sidescan and bathymetric sonar outputs, magnetic anomaly and currents measured by DVL). In order to measure bottom-to-surface profiles of water properties such as salinity or temperature, the UUV must travel through all of that water. In areas with complicated flow characteristics or fronts between different bodies of water, this can lead to undersampling of the environment. Missions designed for collection of environmental data can therefore be very different from NMCM survey missions. The UUV missions developed for seabed survey for NMCM are planned with systematic coverage, overlapping sidescan swaths and at optimal altitude for sidelooking imaging, to ensure that there are no coverage gaps and to meet remaining risk criteria calculated from sensor probability of detection and range performance parameters. Missions run for the collection of environmental data may have different constraints on coverage—it may not be necessary to cover an entire operations area, for example, a set of sparsely spaced singlebeam bathymetric profiles running perpendicular to a shoreline may contain enough data about the approaches to inform placement of an access lane to the beach.

Figure 1: Planning UUV missions and PMA at Hell Bay 4 (photos: Cmdr. S. Carrizosa).


3 Aspects of NMCM UUV operations which can be impacted by environmental effects

The purpose of this section is to highlight the importance of knowledge of the environment to NMCM sidescan sonar survey operations, where the goal is to increase probability of success, i.e. of detection and/or classification of seabed objects of interest, with confidence in the determined positions of these objects. This discussion is directed toward UUV operations, where operators do not have access to the incoming data as it is being collected, but can only examine it after post-mission download, though some aspects also apply to towed sonar operations. With towed sidescan systems, operators typically have live displays of incoming sonar data, system status and navigation, showing coverage, and can replan missions while underway if required.

Operational NMCM is performed in stages or phases and the environment can have impact on all of them, from the initial detection/classification, through the multiple reacquisitions required at each following stage, to final verification if neutralization has been done. The focus of this Section is the environmental effects on operations with small UUVs and on the sensors they can carry, primarily the sidescan sonar systems that are typically used in area survey, for detection and classification.

Sonar performance: NMCM survey missions are planned to meet statistical criteria based on calculated percentage clearance, based on sonar swath coverage and predicted sonar detection performance, based on bottom type and clutter density Figure 2. If the actual sidescan sonar maximum operating range is less than expected, due to differences in water temperature or salinity from what was assumed, presence of sound velocity gradients, or due to seabed slope, then the realized coverage will be less than what was specified in the calculation for the spacing of that set of mission tracks. The mission survey that is performed will not meet the specified percentage clearance criteria. Experience in analysis of the resulting sidescan sonar data is required to recognize when the usable swath width is actually less than the programmed sonar range setting. Figure 2 illustrates an example of this effect on sidescan sonar data collected using an Iver3 UUV. Multipath contamination, probably due to presence of a sound speed gradient, is visible as wavy banding at the outer edge of the swath, limiting the acrosstrack range of good quality data to 25–30 m. The probability of detection between 30 and 50 m is much lower in this case than an operator might assume, based on sonar performance in better operating conditions.


Figure 2: Example of sidescan sonar data negatively affected by environmental conditions.

Navigation error: Similarly, if the UUV is unable to follow the prescribed mission tracks, for example due to strong currents, then the mission even if completed may not meet the criteria. The Standard Deviation on Navigation Error (SDNE) factor accounts for navigational uncertainty in mission planning, but is not intended to account for systematic offsets, e.g., a consistently Westward drift. Navigation error can also be in the vertical direction. UUV sidescan survey missions are planned at a specific altitude to optimize sonar imaging performance. If the buoyancy trim of the vehicle is such that it cannot dive due to changes in water density, even if it completes the mission surfaced, the collected sidescan sonar data will have poor quality. In areas where the water is too shallow for the UUV to maintain optimal altitude, it will run surfaced. Contacts identified in Post-Mission Analysis (PMA) are located in the sidescan sonar imagery using the accompanying navigation data—if this navigation data is of poor quality, then reacquisition during the follow-on stages takes longer or the wrong object is pursued.

The previous discussion included examples where missions were completed, but the resulting sonar survey data did not meet the mission objectives. As stated earlier, it is most likely in UUV operations that deficiencies in survey data quality like these will not be evident until PMA is underway. It may not be possible to replan, redeploy and repeat a mission, depending on the operation and time constraints. Following is discussion of cases where the UUV does not complete the mission at all.

Mission aborted, incomplete: Even the most basic UUVs have system fault failsafe behaviours for self-protection in situations such as run down batteries, detected leak or critical onboard system failures. It is quite possible to program a mission that, for example due to encountering unforeseen currents or other environmental conditions, uses more than the allowable percentage of vehicle battery capacity. The mission will not be completed. Depending on the sophistication of the UUV onboard fault sensing, mission aborts can happen for other reasons, such as excessive pitch and/or roll motions that could be caused by snagging seaweed or flotsam. Another related case of this type would be a mission planned


using incorrect geographical information or charts, for example where a sand bar or other unexpected obstacle prevents the UUV from completing the mission as planned. A few commercially available UUVs are equipped with obstacle avoidance sonars, but this is rarer, so this sensor was not listed in Table 1.

Loss of asset: Though very unlikely, it is possible that a UUV can be lost during a mission. An example of this would be if batteries ran farther down than the allowable percentage due to currents, and then the surfaced UUV drifts off before it can be recovered. If not equipped with satellite or other long range communications, it may not be possible to locate the UUV if it has travelled far. A UUV could become entangled in fishing gear or kelp underwater. When an asset is lost, so is the onboard intelligence, for example Automated Target Recognition (ATR) algorithms [7], vehicle autonomous behaviours, the programmed missions and any recorded data files on the internal storage.

Weather/sea state limits on operations: The foregoing discussion has assumed that the UUV has at least been launched. Once underway, UUVs are largely unaffected by topside weather, at least when running at depths more than a few meters from the surface, and even if surfaced briefly for GPS fixes. Safety of personnel in the support boats, however, is a concern. Most of the boats used for UUV on-water support at the Hell Bay trials were 8-m Rigid Hull Inflatable Boats (RHIBs), which clearly have sea-state and weather limitations on safe operation. Launch and recovery of small UUVs from RHIBs may require leaning over the side of the boat and lifting the UUV over the pontoon. The limits on UUV operation at this point become the limits on safe operation of an open RHIB, and the requirement for crew safety in UUV launch and recovery. During Hell Bay 4, the hosts QinetiQ (UK) supplied one of the range craft, Quasar, which has a barrier-free aft deck, making deployment and recovery of UUVs somewhat easier, and covered cabin space, which allowed for operations in less favourable weather conditions.


Figure 3: Recovering an Iver2 in Loch Alsh, Hell Bay 4 (photo: Cmdr. S. Carrizosa).


4 Small UUVs and sensor fits for environmental measurements

The type of small UUV under consideration here is one- or two-person deployable. Most of the UUVs used in the Hell Bay trials were L3 OceanServer Iver3s [6], during both the environmental pre-trial surveys and the follow-on MCM activities. REMUS 100 [9] UUVs were also involved in the UMS KTA serials. DRDC maintains and operates several Ivers that support ongoing research in the EmTechNMCM project and that were part of the multi-national UUV fleet at the Hell Bay trials. Photos of Iver3 and REMUS 100 UUVs at Hell Bay 4 are shown in Figure 4. This type of small UUV has the advantage of being easily deployable and somewhat covert, not requiring a large launch-and-recovery craft with lift capability, however the small size does limit the payload capacity (computers and sensors), endurance (batteries) and ability to operate in currents.

Figure 4: Small UUVs at the Hell Bay 4 trial. (left) 4 Iver3 UUVs being prepared for an environmental survey (photo: Cmdr. S. Carrizosa). (right) 3 Iver3 and 4 REMUS 100 UUVs at the

UMS KTA MCM trial (photo: UMS KTA).

Following is a summary of the most common small UUV sensor fits that are applicable to the environmental measurements listed in Table 1. Not included are other navigation, safety and communications sensors typically found on UUVs, such as Global Positioning System (GPS) receivers, command-and-control radios (VHF, WiFi), acoustic transponders and modems, and satellite communications equipment (e.g., Iridium).

Sonar: Almost all small UUVs carry some form of either sidescan or multi-beam sonar, aside from those that are specifically designed for water quality monitoring or other specialized purposes. More advanced sidescan-type sonars include interferometric sidescan systems that provide bathymetric measurements across the sonar swath width, or Synthetic Aperture Sonar (SAS) systems that at this time usually require a larger UUV platform. Multi-beam sonars are designed for bathymetric measurements, but can also provide sidescan-like seabed imagery from the backscattered acoustic intensity signal. The sensing beam geometry of multi-beam sonar covers an angular sector to each side of nadir, so that in littoral NMCM


applications, swath width is limited by UUV altitude in shallower water depths—typical multi-beam swath width equals two times sensor altitude or less. Side-looking interferometric systems have much wider swath width, though generally have the same nadir coverage gap as sidescan sonars. Sidescan sonar survey missions for the purpose of environmental characterization are performed differently than NMCM minehunting missions, as discussed previously in Section 2.

Doppler Velocity Log (DVL): This sensor is part of the suite of sensors used for underwater navigation, measuring platform velocity relative to the fixed seabed below. These velocity measurements are used in dead reckoning or more sophisticated algorithms to track UUV position while underwater, where GPS signals cannot be received. Some DVLs have the capability of functioning as an Acoustic Doppler Current Profiler (ADCP), which measures vertical profiles of water currents while the vehicle is underway. This typically requires a special ADCP operation mode since the transmitted acoustic pulses used for current profiling are usually different than those used for bottom tracking.

Altimeter and depth sensors: These are critical parts of the navigation sensor suite onboard the UUV and can also provide single-beam echo sounder water depth measurement capability (vehicle depth + altitude = total water depth). Often altimeter functionality is provided by the DVL. Depth is measured by sensing water pressure.

Conductivity-Temperature-Depth (CTD) and Sound Velocity (SV) sensors: Some UUVs are equipped with dedicated sound velocity sensors and others sense ambient temperature, conductivity and vehicle depth. Conductivity is directly related to salinity, which along with temperature and depth allows calculation of water density and sound velocity. There are also sensors which measure sound velocity directly (acoustically). Water density affects buoyancy of UUVs—small UUVs do not typically have variable ballast systems and have limited ability to maintain altitude in conditions where water density changes more than a very few percent while underway. Both horizontal and vertical gradients in water density, such as at river outflows, affect vehicle navigation. Sonar range performance and data quality, as well as acoustic communications, can all be impacted by refraction effects in areas where there are gradients of water properties.

Camera: Where visibility conditions permit (light level, water clarity), a camera can provide verification of obstacles, seabed type, cover and complexity. Since UUVs are not capable of hovering, the usefulness of cameras on UUVs is limited for object identification or close inspection. Water turbidity is a major limitation for cameras, even those equipped with lighting, particularly in most harbours.

Other sensors: To provide a more complete accounting of UUV sensors, a few others are included here, though these have less bearing on planning for mission success of NMCM sidescan sonar survey missions.

Magnetometer: Metallic objects can have a magnetic signature which provides differentiation from other natural clutter objects (rocks, corals). Buried metallic objects can also be detected this way. Magnetic sensors for small UUVs have recently become more common commercially.

Inertial Measurement Unit (IMU) or Inertial Navigation System (INS): This is a critical component of the vehicle navigation system that senses attitude (pitch, roll, yaw, heave) by sensing lateral and angular accelerations of the platform. This is required information for accurate vehicle navigation and also for


sonar data post-processing. As an environmental sensor, the IMU data output can provide insight into current or wave-induced motions of the vehicle.

Sonde: This is an instrument that measures water quality parameters, such as dissolved oxygen, chlorophyll, pH, turbidity, nitrates, optical backscatter, etc. In a wider NMCM context, information about water clarity and quality is useful for follow-on tasks by divers or Remotely Operated Vehicles (ROVs).

Clock: Accurate time stamping of recorded data is very important, and typically computer clock time is used between GPS position/time fixes.

Most UUVs record lower volume sensor data streams, such as from a CTD or depth sensor, in text log files as comma-separated variables, or asynchronously as data message strings are received by a logging process running on the UUV main computer. Sensors producing large volumes of binary data, such as sonars, DVLs or cameras, record straight to separate data files, usually in Original Equipment Manufacturer (OEM) proprietary format, requiring specialized software to read, view and process.

The environmental sensors themselves can be affected by the environment. Strong sound speed gradients affect sidescan sonar performance, as already seen in Figure 2, but can also negatively impact other acoustic devices such as the DVL. In extreme cases, if acoustic range is strongly limited by adverse propagation conditions, this can prevent the DVL from tracking the seabed, affecting navigation and current profiling performance dramatically.

Figure 5: Range craft (Quasar) and two 8-m RHIBs used during Hell Bay 4 (photo: Cmdr. S. Carrizosa).


5 Examples of environmental data products collected using small UUVs

The following subsections illustrate examples of environmental data products that were prepared from data collected using UUVs during the three pre-trial Hell Bay environmental survey exercises. These were prepared on-site by representatives from: commercial suppliers (Klein Marine Systems, Edgetech, HYPACK, L3 OceanServer, SeeByte), US Navy personnel operating the UUVs and PMA specialists (NOSWC, NOMWC, FST), and scientific personnel (US: NUWC, NRL; UK: Dstl; CAN: DRDC).

A consideration in preparation of these data products is what is most useful for the follow-on NMCM planners. Information is not useful if it is presented in a format that is too complicated to understand quickly or if it is not relevant in the first place. Too much information can also be an issue, as operators can be overloaded or confused.

5.1 Bathymetry

Depth of water is a quantity of fundamental importance in mission planning for both towed and UUV sidescan operations. Towed systems require navigable water depth for the towing craft, including the manoeuvring room around turns. Consideration of tow cable handling speed needs to be given in areas with sloping seabed for conventional passive towed systems and those that can actively maintain altitude since both have a maximum rate of climb that cannot be exceeded by speed over slope. Navigational charts used in mission planning may be unreliable, outdated or inaccurate for reasons such as dredging, construction or natural movement of sediment. In Canada’s Arctic, there are regions that are uncharted altogether.

Figure 6 shows bathymetry data collected in support of the Hell Bay 1 operations outside of San Diego (SPAWAR) in 2013. The Edgetech and Klein sidescan sonars are interferometric, while the Imagenex Delta-T is a multi-beam sonar. Most noticeable is the difference in swath coverage between multi-beam and interferometric sonars. The swath width of multi-beam systems is limited by sensor altitude and water depth in shallow water. At an altitude optimized for sidescan sonar performance, usually 5–10 m, interferometric systems can have the same swath width as a sidescan system if topography and water conditions are conducive (50–75 m per side is typical), while a multi-beam sonar typically has swath width twice altitude, or 10–20 m in this case. In the example shown in Figure 6, three UUVs were deployed almost simultaneously on missions each covering a third of the roughly triangular operations area. Depending on the goal of the operation, the less than complete coverage of the multi-beam sonar data may not be an issue. For the purposes of mapping the local bathymetry to a level that provides overall awareness of water depth features, slope and large scale obstacles such as sand bars, a level of coverage like that shown in Figure 6 is adequate and comes at significantly less cost in data download time, processing time and effort. Even single-beam (altitude + depth) coverage may be entirely adequate. This is an example of a situation where more information is not necessarily better.


Figure 6: Comparison of bathymetry data collected off San Diego using 3 Iver UUVs with different sonar systems (Klein, Edgetech and Imagenex Delta-T) during Hell Bay 1. Chart depths are in fathoms.

The bathymetry data products that were prepared during the Hell Bay trials were provided as georeferenced colour-scaled images, suitable for use as chart overlays in the UUV mission planning or other software, like the example shown in Figure 6. Production of these images involved processing of the bathymetry data using specialized software by highly trained users (this is discussed further in Section 7).

5.2 Currents

Presence of strong currents can impact mission effectiveness, or even success, for both towed and UUV sidescan sonar surveys, as discussed in Section 3. Most small UUVs have a maximum speed of four to five knots, and running at maximum speed depletes battery power more quickly than normal mid-speed operation. Conversely, a current can be used to advantage to conserve battery power if it has been mapped and the mission is planned to account for it.

In the littoral environment, currents can form due to river outflow, local topography (e.g., rip currents offshore of beaches), due to large scale geomorphology along coastlines, driven by wave or tidal forcing. Currents can have vertical structure and be stronger near the surface or at depth, or in the case of tidal currents, can vary over time in both strength and direction.


The primary sensor for measurement of currents on UUVs is the DVL, as discussed in Section 3. Secondarily, platform and navigation information could be used to infer currents, e.g. discrepancy between motor revolutions and speed-over-ground (currents pushing the UUV faster or slower than the motor speed would indicate), or relation of steering motion to counter cross current. This can be very inaccurate, however, if the discrepancy is due to inaccuracy in tracking UUV position, rather than the effect of current. If current measurement is a priority in the mission, UUV profiling behaviours can be used, where the UUV undulates vertically up and down through the water between depth set points while underway to cover the full water depth. It is common practice in UUV mission planning to surface during turns for GPS fixes and the rise and descent for the fix can also provide vertical profiles.

During the Hell Bay environmental characterization trials, water currents were measured using UUVs, bottom mounted upward-looking ADCPs and during Hell Bay 4, the UK deployed downward-looking ADCPs on moorings. Tide and current model results were provided daily by US collaborators (NRL Stennis) and were later compared to the ADCP measurements. Current data products from the UUV measurements and model results were posted to a web repository same or next day, while the bottom-mounted and moored ADCP measurements were downloaded from the instruments on recovery, then posted. Deployment of a bottom-mounted or moored sensor in an area may not be an option in an operational scenario. The primary purpose of the deployed ADCPs was to verify the UUV measurements and model results, and secondarily to provide operational data products.

Figure 7: Currents measured by UUV (green arrows) plotted on top of vehicle track (blue line), overlaid on a chart. A scale arrow for the currents is difficult to see, drawn across the top of the rectangular mission area.


Figure 7 illustrates an example of a UUV-measured current data product from the Hell Bay 4 SMRT exercise. The currents measured by the UUV on-board DVL at a range of 2 m below the vehicle are plotted, so the water depth of the currents, shown by the green arrows on the blue vehicle track, varies with the vehicle depth along the mission track. Also, the duration of the mission was 2 hours 20 minutes, through high tide, so that the direction of tidal flow reversed between the start of the mission (lower right) and completion (upper left). The bottom-mounted ADCP measurements showed that frequently there were opposing currents in the deep and near-surface waters during the maximum tidal flows. Acoustically measured current data is typically very noisy, particularly when measured from a moving platform. All of these factors make interpretation of this data very difficult.

A more useful current data product that was provided during Hell Bay 4 was a summary spreadsheet that presented UUV-measured current profiles—an example screenshot is shown in Figure 8. Most UUV missions included segments where the vehicles came to the surface during some of the turns to reacquire GPS signal, so profiles of water properties were collected while surfacing and returning to depth. Special segments were also included in some missions where the UUV undulated in depth along a straight leg. The UUV onboard DVL measures currents below the vehicle only. In the summary spreadsheet, the measurement time is reported relative to the tide, since that is the dominant current feature in the Loch. Average strengths of the current at the surface, bottom and mid-water are reported, and the profile information is plotted. This format was developed over several Hell Bay trials to provide the most useful current features relevant to UUV operations in a clear and easy to understand manner.


Figure 8: Screen shot of a current profile spreadsheet prepared from UUV-measured current data during Hell Bay 4.


Another current data product that was provided during SMRT was a short overall summary document that captured the main features of the observed current environment, compiled post-recovery of the deployed ADCPs and after a week of operation of the UUVs and model runs. This is included as Annex B of this report, even though the measurements reported in it are not all collected using UUVs. This short document summarized: the largely tidal nature with stronger wind-driven flows in the upper 2 m; potential for opposing flows at surface and bottom at change of tide; and average and maximum observed flows in the area (0.2–0.4 knots typically, with 0.8 knots maximum observed in wind-driven current near the surface). At the southern inlet of the Loch, crossing the southern boundary of the designated Operations Area, there were quite strong tidal flood in-flows—the NRL model showed surface currents greater than 4 knots at maximum tidal current. This is a valuable piece of information, as small UUVs would not be able to navigate against that current.

The final example of a current data product, shown in Figure 9, illustrates the current profiling capability of the Iver3 on-board DVLs with a curtain plot of the timeseries of profiles plotted along the UUV track. This is a product in development and was not provided as part of the environmental data packages during the Hell Bay trials. The Iver3 that was used to collect this data has both downward- and upward-looking DVLs. The thick black line is the vehicle path through the water column plotted against alongtrack distance and the thinner black line is the total water depth (the seabed). The data was collected in the Patuxent River estuary during the Hell Bay 3 exercise. The DVLs were both set to profile out to 5 m range and the UUV was travelling on the surface between 0 and 125 m and between 950 and 1200 m alongtrack, and at the end of the mission. The current velocities shown have been corrected for the horizontal motion of the UUV, however not for vertical motion, evident where the UUV is diving or surfacing under power and pitched—this is an issue with the processing which will be addressed in the future. The UUV was rising unpowered during the final ascent, with horizontal attitude, so the vertical velocity contamination due to non-zero pitch angle is not present. The measured currents show small river flow, mostly 0.3 m/s (0.6 knots) or less, with evidence of stronger flow at 250–300 m alongtrack, at the start of an upslope in water depth.

Figure 9: UUV-measured current profiles (downward- and upward-looking) in the Patuxent River estuary, Hell Bay 3. The heavier black line is the vehicle vertical position along

the track and lighter black line is water depth.


The current data products shown here (Figure 7 to Figure 9 and Annex B) were prepared using a mix of vendor proprietary software, Matlab and Excel. The quickest method would use the UUV mission planning software (VectorMAP) to overlay vectors of current measurements stored in the mission log files, similar to the product shown in Figure 7. Other styles of display, e.g. curtain plots of profiles and spreadsheets, have been investigated since the current vector overlay is difficult to interpret for the reasons discussed.

5.3 Water properties—temperature, salinity and other

As described in Section 2, properties of the local water affect mission effectiveness by controlling UUV buoyancy and sonar performance. Sensors onboard the UUV can only sample properties of the water that they pass through, so in order to measure bottom-to-surface profiles, the UUV must transit the entire water column. This can lead to under-sampling in areas with complicated flow patterns.

During the Hell Bay trials, most water property data products were produced using a feature of the UUV mission planning software which allows plotting of data logged during a mission following the vehicle track, overlaid on a chart. Examples from Hell Bay 4 are shown Figure 10. The UUV executed a mission that started far south of the Operation Area, with a long (3.6 km) transit through the southern inlet and into the Loch. This Iver3 was equipped with a sonde that measured water properties such as temperature, salinity (calculated from conductivity) and dissolved oxygen, shown in Figure 10, and also turbidity, suspended and dissolved solids. The mission was planned and timed to account for the strong tidal in-flow that was indicated by the NRL model output.

The examples shown in Figure 10 were produced using the UUV mission planning software (VectorMAP) which allows plotting of data values read from the recorded mission logs. Data values are colour coded and plotted as a chart overlay at the geographic location where recorded along the UUV track.


Figure 10: Water properties (left to right, temperature, salinity and dissolved oxygen) sampled by UUV while underway on a long ingress mission during Hell Bay 4. Colour-coded values

are plotted along the vehicle mission track.

5.4 Bottom cover, clutter

The primary sensor for providing seabed characterization information is sidescan sonar. Missions designed for providing environmental seabed information are planned differently from NMCM missions. During Hell Bay 4, a sub-section of the Op Area was surveyed with greater than 100% coverage and PMA was performed to determine clutter density and to provide other observations of relevant seabed characteristics. The results were provided as PowerPoint slides, such as the example shown in Figure 11. The sidescan sonar data PMA and processing to produce image mosaics was done using specialized software (SonarWiz), and resulting seabed imagery was exported to include in the slides. The images shown in the slides are not particularly useful in this form (overlapping swaths and low resolution), but do show the extent of the area that was analyzed for clutter density. Since the follow-on NMCM and ATR exercises were intended to be blind, without revealing the ground truth positions of the deployed targets until afterward, it was agreed not to disclose any positions of targets if any were found in the seabed imagery collected during SMRT. The time required for preparation of the material shown is included on the left side of the slide. This will be discussed further in Section 7.


Figure 11: Results of PMA of sidescan sonar data collected in Hell Bay 4 to determine clutter density in a sub-section of the Op Area (graphic prepared by US FST).

5.5 Obstacles

While not strictly an environmental parameter, one of the data products that was produced during the Hall Bay 4 SMRT exercise was a chart overlay showing a No-Go area of heavy concentration of fishing gear in the northwest corner of the Op Area. The boundary of the area was mapped out by placing an Iver3 UUV on the aft deck of one of the support boats and piloting along the edge of the area while logging in mission mode so that the recorded GPS track data mapped out the boundary. This track was then plotted in the mission planning software, shown in Figure 12. In the figure, the green line is the track of the vehicle following the outer boundary of the No-Go area containing fishing gear, the Op Area is the pink rectangle with yellow numbered corners and the transparent red shading was added to the screenshot later (in PowerPoint) to highlight the No-Go area. The chart symbol “#” indicates “foul ground” meaning an area with gear on the seabed making it unsuitable for anchoring or trawling.


Figure 12: No-Go area containing a high concentration of fishing gear, mapped using a UUV (graphic prepared by US FST).

5.6 Magnetic anomaly

The presence of a magnetic anomaly can differentiate between man-made and naturally occurring seabed objects. During the Hell Bay 1 trial, magnetometer data was collected using a small system towed by an Iver2 UUV, with example results shown in Figure 13. The magnetic field strength has been contoured (white lines) and plotted over mosaicked sidescan sonar imagery. Three areas of enhanced magnetic anomaly are evident, two associated with large ship anchors that are clear in the sidescan image mosaic, and a third that is less obvious in the sonar imagery, but is probably a third anchor mostly buried. The contouring of the anomaly data is very coarse, since the magnetic measurement locations are on the UUV tracks which cross the area horizontally (East-West) at the positions marked by the blue arrows. This type of scalar quantity data would perhaps be more accurately depicted by the kind of plot shown in FFigure 10, with a colour-coded vehicle track line.


Figure 13: Contoured magnetic anomaly data (white lines) overlaid on a sidescan image mosaic. The locations of the East-West UUV mission tracks are shown by the blue

arrows (graphic prepared by HYPACK, Hell Bay 1).


6 Use of autonomy

Almost all small UUVs have a basic level of autonomy in the ability to follow a set of waypoints to execute a mission in the absence of radio communications or GPS signal (i.e., underwater). “Autonomy” in the context of this discussion refers to a higher level of programmed in situ decision-making ability. An example of this is mission re-planning behaviour that automatically adjusts the direction of subsequent sidescan sonar survey tracks to be perpendicular to the dominant ripple crest orientation [10]. Looking down the along-crest direction allows more effective detection of objects lying on a ripple field. Another example provides more sophisticated fault tolerance in managing low battery situations. Research is ongoing into very complex multi-vehicle collaborative autonomous behaviours which can allow sharing and reallocation of work load—this requires some level of underwater communications between platforms.

A very interesting possibility for mapping environmental features using UUVs has been explored by Petillo et al. [11][12]. They have developed UUV behaviours for what they describe as Autonomous Adaptive Environmental Assessment (AAEA). The overall concept is that the UUV autonomously navigates based on incoming sensor data in real time to, for example, follow the edge of an oceanographic front of a quantity such as salinity or temperature. When a set point value for a sensed quantity is encountered, the UUV executes a turn in alternating directions, so that an approximate contour can be built up be consecutively crossing and returning to that sensor output value while underway.

During the Hell Bay 4 trial, an autonomous environmental mapping behaviour under development by NUWC was tested in which a UUV follows a specified depth contour. The two UUV tracks shown in Figure 14 follow the 20 m (green) and 5 m (brown) water depths. Note that the underlying chart shows water depth contours at lowest low tide and the UUV missions were run at mid-to-high tide, with 3–5 m tidal range in this area. This type of selective bathymetric survey, tuned to map a particular depth contour, can be conducted in a fraction of the time of a conventional bathymetric sonar survey, using a minimally equipped UUV, and requires very little post-processing to produce usable information.


Figure 14: Chart showing tracks of two UUVs executing contour-following behaviour during Hell Bay 4. The green line follows 20 m water depth and the brown line follows 5 m.


7 Software and training considerations

Preparation of the environmental data products that have been shown in this report required varying degrees of skill, training and effort. Table 2 lists the commercial software that was used to process the different data types and produce the examples shown in the Figures.

Table 2: Software used in preparation of data products shown in this report.

Software Description Product Figure Nos.

Level of training

VectorMAP [13] (L3 OceanServer)

Mission planning and post-mission logged data display for Iver UUVs

Missions, scalar quantity plots from vehicle logs, overlay of georeferenced image layers, e.g. charts and mosaics

8, 10, 12 M

SonarMosaic (L3 OceanServer)

Mosaic sidescan data for sonars fit to Iver UUVs

Georeferenced sidescan sonar mosaic chart overlays

9 M

Underwater Vehicle Console (L3 OceanServer)

Load/initiate missions, control sensor and vehicle settings, vehicle interface

Operation of Iver UUVs, including execution of missions

All H

HYPACK [14] Multi-beam bathymetry, sidescan sonar and other data processing

Color-scaled georeferenced mosaics of processed sonar and other data (e.g., magnetometer)

4, 11 H

SonarWiz [15] (Chesapeake Technology)

Mosaic sidescan and bathymetric sonar data

Color-scaled georeferenced mosaics of processed sonar data

9 H

Excel (Microsoft) Data manipulation, plotting, spreadsheet calculations

Tables, plots 6 L

PowerPoint, Word (Microsoft)

Presentation of data products and analysis

Annotated slides, documentation, reports

9, 10 L

Global Mapper [16] (Blue Marble Geographics)

Geographical Information System (GIS) for plotting georeferenced data

Chart overlays, plotting of georeferenced data products

4, 12 M


Software Description Product Figure Nos.

Level of training

SonarPro [17] (Klein Marine Systems), Discover [18] (Edgetech), Yellowfin, Delta-T [19] (Imagenex), Scanline [20] (Tritech)

Sonar data viewers provided by OEM with respective UUV sonar fits

Contact locations in sonar imagery (targets, clutter), seabed texture, sonar data Quality Control (QC) and PMA

9 M

Matlab [21] (Mathworks)

Scientific data processing, analysis and display

Plots, scientific analysis (e.g., statistics), georeferenced imagery

5, 7 H

The far right column in Table 2 indicates a rough assessment of the operator training level required to use the software to process data and produce output products. “L” indicates a low level—most people would know, or be able to figure out, how to use Microsoft Word, for example, sufficiently well to produce sentences of text with accompanying cut-and-pasted images. “M” indicates a higher level, and in the cases of the L3 OceanServer and OEM sidescan sonar viewer software, operators would have learned how to use these in the course of being trained to operate the UUVs (this will be discussed further later). “H” indicates specialist training is required, and considerable experience. HYPACK and SonarWiz, both used for sonar data processing, offer training courses in durations of a few days to a week, and it takes time working with these highly specialized tools to be efficient and effective in their use. The designation of “H” for the Underwater Vehicle Console software (L3 OceanServer) includes training on vehicle operation beyond just using the interface software. Matlab is scientific analysis software that operators will likely never see—it is used as a research and development tool, and was only included here as it was used in development of data products shown in this report. Also not included here is SeeTrack (SeeByte) [22], which is an integrated UUV mission planning, monitoring, autonomy and PMA software tool which can interface with multiple different types of unmanned vehicles. SeeByte participated in the Hell Bay 3 exercise to demonstrate their Common Operator Interface for Navy (COIN) system, which is a plug-in for SeeTrack.

UUVs are highly technical and specialized pieces of equipment requiring significant training and experience to use and maintain. A typical small UUV could be described as follows: computer(s); control system including actuators and propulsion; sonar; DVL(s); GPS receiver; INS; VHF and WiFi radio, acoustic (perhaps satellite) communications suites; locating transponder/pinger; batteries (usually lithium-ion); perhaps a camera and/or sonde or CTD; running lights; all integrated into a 6–8 inch diameter depth rated housing, with O-ring seals and underwater connectors. L3 OceanServer offers one week (or longer) training sessions with the purchase of their vehicles, during which time operators are shown how to do routine maintenance and to program and run missions with the specific sensor fits on their vehicles. Each one of the vehicle sub-systems could be the subject of a training course on its own. During each of the Hell Bay trials, representatives from L3 OceanServer were onsite providing engineering and data processing support to the operators, who themselves had prior training and experience in exercises. Representatives from both Klein and Edgetech were also present at Hell Bay 3 to assist with sonar operations, as well as personnel from HYPACK and SeeByte to help with sonar data


processing. UUV operators during the three Hell Bay environmental survey exercises included members of the US Navy Fleet Survey Team (FST), Naval Oceanography Special Warfare Center (NOSWC) and Naval Oceanography Mine Warfare Center (NOMWC). These individuals have been provided with OEM training on the UUVs and required software, and engage in several training exercises per year to maintain that training, as often as quarterly.


8 Manning and tempo considerations

It was a stated goal for each of the three Hell Bay environmental characterization exercises to provide data products on a 24-hour cycle, from mission planning to posting prepared data products to an online repository. This was in part to fulfill training requirements for the US Navy operators of the UUVs, but also of interest to the TTCP participants as a proof of concept. The Hell Bay 4 SMRT exercise provided a good example of how this requires a large team. The same individuals who had training for mission planning were also involved in the PMA and generation of data products, so that made for very long days for key individuals. The trial plan schedule included contingency for weather, if on-water activities were not possible at times due to inclement conditions, however the weather was good for almost the entire duration (winds were too high for one morning between September 10 and 17) and personnel were wearing out.

Figure 11 includes information, repeated here in Table 3, on the time taken to perform various stages in the preparation of that data product, a sidescan sonar survey of one part of the Op Area. Note that the total time shown does not include the transit time to get to the survey site and back, about 2 nmi (nautical mile) each way, but does include the time to deploy and recover the UUV (less than half an hour). During the time that this survey was being performed, two other UUVs were surveying simultaneously, covering other parts of the Op Area. Three other surveys were performed earlier in the day, also operating simultaneously. The planning and processing time for sonar surveys is comparable to the time required to perform the survey in most cases—other environmental data products generally take less time to prepare. This is a motivating factor behind the development of automated, or even on-board, processing for sonar data. Also note that the data download time, one hour in this case, is a significant bottleneck encountered particularly with high volume sonar survey data, which UUV suppliers are working to address (implementation of USB 3.0 and larger solid state, or swappable, data drives on board).

Table 3: Time requirements for tasks in production of the data product shown in Figure 11.

Task Time required (hrs)

Mission planning (VectorMAP) 1.5

Mission execution 3.5

Data download 1

Data processing (SonarWiz, SonarMosaic) 0.5

Analysis/editing 2

Product generation (Powerpoint) 0.5

Total: 9


Taking the final Hell Bay exercise as an example for a discussion of manning, the UUV support boat crew included a coxswain (specialists from US Navy EODMU8) and one or two UUV handlers at minimum (US FST or NOSWC). At times, other personnel were onboard for deployment of, for example, wave drifters or other environmental sensors, however as shown in Figure 4, there was not much deck room for extra personnel when several UUVs were onboard. The teams of US Navy operators and PMA specialists were: one (1) from EODMU8, four (4) from NOSWC and three (3) from FST. Additionally, there was one (1) field engineering specialist from L3 OceanServer and one (1) US reservist (Office of Naval Research liaison officer). Of these, most were involved on shore in preparation of data products on a daily basis, from processing of sonar data mosaics to making meteorological measurements to generating reports. Also involved daily were between three (3) and five (5) scientists (UK, US, CA), developing experimental data products or those which the US Navy specialists did not have experience with, and handling posting of products and model outputs to the web repository. In summary, the on-water teams consisted of two (2) or three (3) personnel per boat, with up to three (3) boats operating at a time (usually two (2)). On land, the PMA team consisted of 8 to 10 people (operators and scientists), fewer during operations if some of these individuals were required on the boats. The total number of personnel on hand during Hell Bay 4 was 19. As already discussed, this number of people was the bare minimum to maintain a 24-hour plan-to-post cycle, with up to six UUVs in operation most days. The 24-hour cycle was largely held, though there were increasing lags in uploading some of the data products toward the latter part of the trial, as the processing backlog was growing and more UUVs were coming into service, operating simultaneously.


9 Conclusion and recommendations

The RCN will be in a position to be looking for advice in this area soon, if not already. UUVs are in the hands of operators now, following the recent successful completion of a procurement process providing Shallow Seabed Intervention Autonomous Underwater Vehicle (SSI AUV) capability to the FDUs. These assets are intended for search, location, and identification of non-minelike objects. This is an opportunity to provide input to planning for the employment for these UUVs, including possible use in Rapid Environmental Assessment (REA), Battlespace Characterization (BC) and Intelligence Preparation of the Operational Environment (IPOE) roles, tasks which are well-suited to UUV platforms. The collection of environmental data benefits situation awareness in an Operational Area, and can be critical in areas such as accurate determination of sonar performance parameters for follow-on surveys.

There is motivation also for continued research into countering environmental effects on UUV operations, for example, improvements in navigation performance and sensor performance assessment using through-the-sensor techniques. Autonomous behaviours have a lot to offer in this regard, in the areas of on-the-fly mission replanning, collaborative multi-platform behaviours, and fault tolerance.

Following is a list of recommendations arising from consideration of the lessons learned during the completed series of Hell Bay environmental characterization exercises, from ongoing discussion among the TTCP collaborators and from continuing follow-on trial activities at DRDC.

Table of environmental parameters: The operator feedback gathered on the parameters in the table validated the thought put into preparing the list. The list of parameters provided a framework for planning of the Hell Bay 4 SMRT effort, but can also advise future efforts and aid in prioritization of research effort. DRDC’s most recent NMCM research project, for example, includes effort in characterization of currents measured using UUVs. This is an environmental characteristic identified as having high potential for impact on UUV mission effectiveness, while at the same time not being a solved problem in UUV operation and technology.

Overview of UUV sensor technologies: This collection of information needs to be kept current, particularly considering the speed of technological evolution. Recent advances in magnetometers and improvements in underwater cameras and lighting are notable. Aside from the listed UUV sensor fits, examples of other areas where advances will have high impact are in battery technologies, smaller faster processors, and improvements to signal processing for sonars and other sensors.

Environmental data products: There needs to be a close relationship with operators to ensure maximum utility of environmental data products. Collaboration with OEM providers may be valuable in investigation of the method and choices of data display offered to operators (e.g., L3 OceanServer’s VectorMAP, and SeeByte’s SeeTrack). Researchers are well positioned to bridge between the suppliers and operators.

Autonomy: Specifically for the purposes of autonomous collection of environmental data, continued close relationship with collaborators who are more advanced in this area (e.g., the US), via TTCP, is recommended. It may be a long time before autonomous behaviours are in general use operationally, however less offensive activities, such as environmental data collection, may offer a gateway for uptake


by operators. Outstanding questions, such as which autonomy framework best positions the research for better uptake by operators or whether OEM built-in autonomous mission options are a better solution, will need to be addressed. Within DRDC’s NMCM research program, cross ties between the Battlespace Characterization (BC) and the Unmanned Systems WBEs will be increasing, which will provide a more direct route to implementation of concepts for autonomous behaviours for collection of environmental data. Investigation by DRDC of the Autonomous Adaptive Environmental Assessment (AAEA) concept described in Section 6 should prove to be of great benefit.

Software and training: DRDC’s NMCM research program can benefit from refamiliarization with the RCN training rotations and the software tools that are coming into use by the UUV operators. Outside Canada, TTCP-enabled collaboration offers the possibility of future attendance at US and UK UUV operator training exercises, e.g. the US Advanced Naval Technology Exercise (ANTX) series, or Office of Naval Research (ONR)-sponsored Foreign Comparative Test (FCT) programs.

Manning and tempo: One of the most practical and important lessons learned in observation of the Hell Bay trials was not to underestimate how many people are required to effectively perform PMA on even modestly sized data sets, particularly for sonar survey data. During Hell Bay 4, when special emphasis was placed on achieving a 24-hour plan-to-post cycle, it was not possible to maintain this for more than a few consecutive days with a total of 19 trained personnel operating up to six UUVs and processing the collected data. This was mostly due to involvement of the same individuals in both the mission planning and PMA phases of the cycle.


References

[1] M. Incze, “TTCP Hell Bay REA,” Final revision 1.0, March 2013.

[2] M. Incze, “TTCP TP13 Hell Bay 3 Trials Plan – Battlespace Characterization KTA,” version 1.1, April 2015.

[3] M. Incze, “TTCP TP-13 SMRT (Hell Bay 4) Trials Plan Battlespace Characterization KTA,” Rev 1.5, September 2016.

[4] Director General Naval Force Development, “Concept for Maritime Unmanned Systems (MUS),” November 2015.

[5] A. Crawford, “Comments from Canadian Operators on the Table of Environmental Parameters,” Defence Research and Development Canada, Reference Document, DRDC-RDDC-2016-D028, July 2016.

[6] A. Hunter, W. Connors and S. Dugelay, “An Operational Concept for Correcting Navigation Drift During Sonar Surveys of the Seafloor,” IEEE Journal of Oceanic Engineering, Vol. 43, Issue 4, pp. 913–926, October 2018.

[7] P. Chapple, “Automated Detection and Classification in High-resolution Sonar Imagery for Autonomous Underwater Vehicle Operations,” DSTO-GD-0537, December 2008.

[8] L3 OceanServer, “Iver3 Standard AUV,” https://ocean-server.com/iver3/ (Access date: March 18, 2019).

[9] Kongsberg Maritime, “Autonomous Underwater Vehicle, REMUS 100,” https://www.km.kongsberg.com/ks/web/nokbg0240.nsf/AllWeb/D241A2C835DF40B0C12574AB003EA6AB (Access date: March 18, 2019).

[10] D. Williams, “AUV-Enabled Adaptive Underwater Surveying for Optimal Data Collection,” Intelligent Service Robotics, Vol. 5, Special Issue on Marine Robotics Part 2, pp. 33–54, January 2012.

[11] S. Petillo, “Autonomous & Adaptive Oceanographic Feature Tracking On Board Autonomous Underwater Vehicles,” Doctoral Thesis in Oceanographic Engineering, Massachusetts Inst. of Technology and Woods Hole Oceanographic Inst., February 2015.

[12] S. Petillo, A. Balasuriya and H. Schmidt, “Autonomous Adaptive Environmental Assessment and Feature Tracking via Autonomous Underwater Vehicles,” IEEE Oceans’10, Sydney, Australia, May 2010.

[13] L3 OceanServer, “VectorMap Mission Planning,” https://ocean-server.com/vectormap/ (Access date: March 19, 2019).


[14] HYPACK, “HYPACK® MAX,” http://www.hypack.com/product/id-HYPACK-MAX/HYPACK%C2%AE-MAX (Access date: March 19, 2019).

[15] Chesapeake Technology, “SonarWiz7,” https://chesapeaketech.com/ (Access date: March 19, 2019).

[16] Blue Marble Geographics, “Global Mapper 20.1,” https://www.bluemarblegeo.com/products/ global-mapper.php (Access date: March 19, 2019).

[17] Klein Marine Systems, Inc., “SonarPro® Software Package,” http://kleinmarinesystems.com/ products/sonarpro/ (Access date: March 19, 2019).

[18] Edgetech, “Discover 4125 User Software Manual,” https://www.edgetech.com/wp-content/ uploads/2016/09/0016652_Rev_E.pdf, ver. 0016652_REV_E, October 2017 (Access date: March 19, 2019).

[19] Imagenex Technology Corp., https://imagenex.com/products/yellowfin and https://imagenex.com/products//837b-delta-t-300-m-120-x-20 (Access date: March 20, 2019).

[20] Tritech International Limited, https://www.tritech.co.uk/support-software/starfish-seabed-imaging-systems-scanline (Access date: March 20, 2019).

[21] The Mathworks Inc., MATLAB (versions R2016 to R2018), Natick, Massachusetts, 2016-2018.

[22] SeeByte Ltd., http://www.seebyte.com/military/seetrack-military/ (Access date: March 20, 2019).


Annex A Table of environmental parameters prepared during planning for Hell Bay 4

Tables A1–A3 are taken from the planning documentation prepared by the active BC KTA members during the preparations for Hell Bay 4 [1][5]. The participating members (UK, US and CA) were provided a draft copy of the tables for review and comment by their respective national MCM operational commands. Reviewing units included:

w Canadian Forces Maritime Warfare Centre (Lead—Mine Warfare Tactics Coordinator, LCdr T. David) (CA)

w Maritime Operations Group 5, Maritime Survey Office (Lead—Route Survey Operations Officer, Lt(N) K. Cunningham (CA)

w Mine Warfare Research Group, DRDC – Atlantic Research Centre (CA)

w EODGRU2 N8 (Lead—Richard Graves) (US)

w EODG-1, N8 (Lead—Cordell Parker) (US)

w COMNECC, N8 (Lead— LCDR Paul Mahoney) (US)

w COMEODGRU ONE, N8 (Lead—LTJG Aaron Bell) (US)

w NAVSEA, SEA 06 PMS 408 (Lead—LCDR Mike Simmons) (US)

Inputs from the national reviews were then incorporated into Tables A1–A3, which were used to drive operational design and mission planning during the pre-trial environmental characterization phase of Hell Bay 4.


Table A.1: Environmental parameters affecting performance of MCM assets operating in littoral waters for each phase of MCM operations and change detection. Only in-water and seabed parameters are

included: meteorological parameters are listed in a separate table.

Table A.2: Meteorological and atmospheric environmental parameters affecting MCM operations.

Table A.3: Environmental factors affecting MCM diving operations.


Annex B Summary report on observed currents during Hell Bay 4

The following document was uploaded to the web repository as part of the environmental data package prepared during the Hell Bay 4 SMRT exercise that was delivered to follow-on MCM mission planners. It is a summary of the current observations from measurements by UUVs and deployed bottom-mounted ADCPs, giving an overview of the observed currents in the Operations Area in Loch Alsh. It was uploaded on the final day of the trial, after recovery of the deployed ADCPs, data download and preliminary processing:


List of symbols/abbreviations/acronyms/initialisms

AAEA Autonomous Adaptive Environmental Assessment

ADCP Acoustic Doppler Current Profiler

ATR Automated Target Recognition

ANTX Advanced Naval Technology Exercise (US)

BC Battlespace Characterization (TTCP KTA)

CA

CAF

Canada

Canadian Armed Forces

COIN Common Operator Interface for Navy (SeeByte software)

CONOP Concept of Operation

CTD Conductivity-Temperature-Depth (sensor)

DND Department of National Defence

DRDC Defence Research and Development Canada

DSTL

DVL

Defence Science and Technology Laboratory

Doppler Velocity Log

EODMU8 Explosive Ordnance Disposal Mobile Unit 8 (US Navy)

FCT Foreign Comparative Test (US ONR-sponsored program)

FDU

FST

Fleet Diving Unit

Fleet Survey Team (US Navy)

GIS Geographic Information System

GPS Global Positioning System

IMU Inertial Measurement Unit

INS Inertial Navigation System

IPOE Intelligence Preparation of the Operational Environment

KTA Key Technical Area

MCM Mine Countermeasures

MUS

NAS

NMCM

Maritime Unmanned Systems

Naval Air Station

Naval Mine Countermeasures

nmi Nautical mile


NOMWC Naval Oceanography Mine Warfare Center (US)

NOSWC Naval Oceanography Special Warfare Center (US)

NRL Naval Research Laboratory (US)

NUWC Naval Undersea Warfare Center (US)

OEM Original Equipment Manufacturer

ONR

PMA

Office of Naval Research

Post-Mission Analysis

QC Quality Control

RCN

REA

Royal Canadian Navy

Rapid Environmental Assessment

RHIB Rigid Hull Inflatable Boat

ROV Remotely Operated Vehicle

RPM Rotations Per Minute

SAS Synthetic Aperture Sonar

SDNE Standard Deviation on Navigation Error

SMI

SMRT

Ship-Mine Interaction

Support of MCM through Rapid Environmental Assessment—Tactical

SOP Standard Operating Procedure

SPAWAR SPAce and Naval WARfare Command (US)

SV

SVP

SSC

SSI AUV

Sound Velocity

Sound Velocity Profile

Stennis Space Center

Shallow Seabed Intervention Autonomous Underwater Vehicle (Program)

TP

TTCP

Technical Panel

The Technical Cooperation Program

UK

UMS

United Kingdom

UnManned Systems (TTCP KTA)

US

UUV

United States of America

Unmanned Underwater Vehicle

VHF Very High Frequency (radio)

DOCUMENT CONTROL DATA *Security markings for the title, authors, abstract and keywords must be entered when the document is sensitive

1. ORIGINATOR (Name and address of the organization preparing the document. A DRDC Centre sponsoring a contractor's report, or tasking agency, is entered in Section 8.)

DRDC – Atlantic Research Centre Defence Research and Development Canada 9 Grove Street P.O. Box 1012 Dartmouth, Nova Scotia B2Y 3Z7 Canada

2a. SECURITY MARKING (Overall security marking of the document including special supplemental markings if applicable.)

CAN UNCLASSIFIED

2b. CONTROLLED GOODS

NON-CONTROLLED GOODS DMC A

3. TITLE (The document title and sub-title as indicated on the title page.)

Use of small unmanned underwater vehicles for environmental battlespace characterization in support of naval mine countermeasures

4. AUTHORS (Last name, followed by initials – ranks, titles, etc., not to be used)

Crawford, A.

5. DATE OF PUBLICATION (Month and year of publication of document.)

February 2020

6a. NO. OF PAGES (Total pages, including Annexes, excluding DCD, covering and verso pages.)

48

6b. NO. OF REFS (Total references cited.)

22

7. DOCUMENT CATEGORY (e.g., Scientific Report, Contract Report, Scientific Letter.)

Scientific Report

8. SPONSORING CENTRE (The name and address of the department project office or laboratory sponsoring the research and development.)

DRDC – Atlantic Research Centre Defence Research and Development Canada 9 Grove Street P.O. Box 1012 Dartmouth, Nova Scotia B2Y 3Z7 Canada

9a. PROJECT OR GRANT NO. (If appropriate, the applicable research and development project or grant number under which the document was written. Please specify whether project or grant.)

01cf - Emerging Techniques in Naval Mine Countermeasures

9b. CONTRACT NO. (If appropriate, the applicable number under which the document was written.)

10a. DRDC PUBLICATION NUMBER (The official document number by which the document is identified by the originating activity. This number must be unique to this document.)

DRDC-RDDC-2019-R106

10b. OTHER DOCUMENT NO(s). (Any other numbers which may be assigned this document either by the originator or by the sponsor.)

11a. FUTURE DISTRIBUTION WITHIN CANADA (Approval for further dissemination of the document. Security classification must also be considered.)

Public release

11b. FUTURE DISTRIBUTION OUTSIDE CANADA (Approval for further dissemination of the document. Security classification must also be considered.)

12. KEYWORDS, DESCRIPTORS or IDENTIFIERS (Use semi-colon as a delimiter.)

Rapid Environmental Assessment; Unmanned Underwater Vehicle; Battlespace Characterization

13. ABSTRACT (When available in the document, the French version of the abstract must be included here.)

DRDC has participated with international (TTCP) partners in pre-trial environmental characterization exercises prior to three out of four of the Hell Bay trials. In each case, environmental data was collected using small unmanned underwater vehicles (UUVs), as well as other sensors, and compiled into a comprehensive data package that was delivered to follow-on MCM exercise participants, to improve odds of success in planned missions. The experience gained in the planning and execution of these substantial pre-trial survey exercises and in collaboration on development of useful environmental data products, was invaluable and serves as an example of the benefits of international cooperation. It is an accepted fact that knowledge of the operational environment is key to success.

This report presents an overview of environmental parameters relevant to follow-on MCM seabed survey operations and potential effects of environmental factors, summarizes current small UUV technology and sensors for making environmental measurements, presents examples of environmental data products that were included in the compiled data packages and a summary of lessons learned.

RDDC a pris part avec des partenaires internationaux (TTCP) à des exercices de caractérisation environnementale préalables aux essais avant trois des quatre essais menés à Hell Bay. Dans chaque cas, les données environnementales ont été recueillies au moyen de petits véhicules sous-marins sans équipages (VSSE) ainsi que d’autres capteurs, lesquels ont permis la compilation d’un ensemble de données complet livré aux participants à l’exercice de LCM suivant afin d’améliorer les chances de succès lors des missions planifiées. L’expérience acquise durant la planification et l’exécution de ces exercices de levé préalables aux essais, ainsi que lors de la collaboration aux fins de l’élaboration de produits de données environnementales utiles, a été extrêmement précieuse et sert d’exemple des avantages que l’on peut tirer de la coopération internationale. Il est reconnu que la connaissance de l’environnement opérationnel est un élément clé du succès.

Le présent rapport donne un aperçu des paramètres environnementaux pertinents pour les opérations de levé des fonds marins dans le cadre de la LCM, ainsi que des effets potentiels des facteurs environnementaux; il dresse un sommaire de l’état de la technologie actuelle des VSSE et des capteurs qui servent à prendre des mesures environnementales, il offre des exemples de produits de données environnementales inclus dans les ensembles de données compilés de même qu’un sommaire des leçons apprises.

use of small unmanned underwater vehicles for environmental … · mike stuckenschneider, lonnie...

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