small airport surveillance sensor (sass) · small airport surveillance sensor - 4 sdc 18 november...

Matthew J. Rebholz

27 October 2015

Small Airport Surveillance Sensor (SASS)

Distribution Statement A. Approved for public release; distribution is unlimited.

This work is sponsored by the Federal Aviation Administration under Air Force Contract #FA8721-05-C-0002. Opinions, interpretations, recommendations and conclusions are those of the author and are not necessarily endorsed by the United States Government.

Sponsor: Matthew Royston, ANG-C52, Surveillance Branch (Andras Kovacs, Manager)

Lincoln Laboratory Air Traffic Control Workshop 2014 Small Airport Surveillance Sensor- 2 SDC 18 November 2014

• Overview

• System Design

• Initial Data Collections

• Summary

Outline


• Runway incursions remain a serious issue at small airports

• Visual surveillance can be impaired by decreased visibility, weather, and terrain

• One-In-One-Out procedures during IMC impacts airport capacity

Surveillance gaps exist at many small airports

Low cost secondary surveillance solutions needed to fill surveillance gaps for small airports

Motivation

Serious Runway Incursions by Airspace Class (2013)

FAA Aviation Safety Information Analysis and Sharing (ASIAS) System


Small Airport Surveillance Sensor (SASS) Architecture

• Provides secondary surveillance of airport surface and nearby airspace • Actively interrogates surface ATCRBS & airborne non-ADS-B aircraft • Receives & validates ADS-B position from 1090ES • Remote Unit can be at airport, TRACON, ARTCC or remote facility


• GA airports with Class D airspace towers – 370 potential airports

• Non-towered airports with substantial traffic – 30 with 100,000+ operations per year

• Potential to fill surveillance not covered by FAA radars or ADS-B

– ADS-B mandate applies to Class B & C and above 10,000’

• Potential to integrate SASS with runway incursion safety logic

• Small footprint that can be located on airport property or deployed as a mobile system for special events

SASS Fills Unique Role

Target Airports

Key Benefits

SASS provides low-cost surveillance capability to either augment, or provide standalone, cooperative airport surface and terminal area airborne surveillance


• Overview

• System Design


• Summary

Outline


Surface Surveillance

Minimum Coverage Area1 10,000 ft long 2,000 ft wide

Position Error (1 σ) ≤ 30 ft

Airborne Surveillance

Range 20 nm Position Error (1 σ)2 ≤ 0.2 nm Range Resolution3 ≤ 60 ft

Preliminary SASS Requirements (Secondary Surveillance)

References: 1. Low Cost Ground Surveillance System (LCGS) Specification. 2. Required Surveillance Performance Accuracy to Support 3-Mile and 5-Mile Separation in the National Airspace System”, S.D. Thompson et al, MIT Lincoln Laboratory Project Report ATC-323,

November 2006. 3. Mode S Sensor Specification, FAA-E-2716, Federal Aviation Administration, 1985


• Passive: Surface Surveillance of Mode S Squitters – Azimuth measurements from both SASS units define two lines of position, θ1 and θ2

– Time difference of arrival (TDOA) defines hyperbola (derived from tRx1 and tRx2) – Geolocation is a least-squares solution that provides best fit to measurements

• Active: Surface/Airborne Surveillance of ATCRBS/Mode S Interrogations – Azimuth measurement from one sensor defines one line of position, θ1 – Time of arrival (TOA) from interrogation and reply, tinterr, provides range – Intersection of both lines defines position

Surveillance Methodology

SASS1 SASS2

hyperbola


Remote Unit

Maximum Likelihood Geolocation Estimate

SASS Sensor B SASS Sensor A

Geolocation Process

Calibration

Sensor B Model Parameters

AOA Surface AOA Surface

TDOA Surface Test Data:

I/Q Samples Test Data:

I/Q Samples

Sensor A Model Parameters

AOA = Angle of Arrival TDOA = Time Difference of Arrival


Modeled Surface Surveillance Error (ft) (Hanscom Field in Bedford, MA)

SASS Sensor

SASS Sensor

Model Assumptions Range error: 10’ (1 σ)

Azimuth error: 0.4° (1 σ)

30’ position error or less over entire surface movement area


Range [nm]

0 10 20 30 40 50 60

Cro

ss-r

ange

[nm

]

0

0.1

0.2

0.3

0.4

0.5Cross-Range Accuracy

Airborne Surveillance Predictions

Range [nm]

0 10 20 30 40 50 60

SNR

[dB

]

0

10

20

30

40

Detection Range

Secondary Surveillance Radar Range Equation

SNR Detection Threshold

Successful detection at 20 nm

Cross-range Accuracy Requirement

• Can successfully detect at 20 nm

• Assuming azimuth accuracy = 0.4º from surface model requirement, we can achieve 0.14 cross-range accuracy at 20 nm (within 0.2 nm airborne requirement)

Meets cross-range accuracy requirement

Cross-Range accuracy assuming azimuth

accuracy = 0.4º


Range Requirements

SASS meets range requirements (10’ for surface and 60’ for airborne)

- Note: 1 ns timing error ≈ 1 ft range error

GPS Time - Hours in the Day

19.4 19.6 19.8 20 20.2 20.4 20.6 20.8

Est.

PPS

Erro

r [ns

]

-15

-10

-5

0

5

10

15

20Timing Error

Gps0: Mean = 2.5 ns, Var = 7.2 ns

Gps1: Mean = 2.4 ns, Var = 6.9 nsDifference: Mean = 0.7 ns, Var = 0.6 ns


• Minimize Maximum Mainlobe Beamwidth

– Azimuthal or direction finding (DF) error proportional to mainlobe beamwidth

• Minimize Maximum Sidelobe

– Smaller sidelobes reduce signal ambiguities

• Design Optimization Technique

– Use Monte Carlo techniques to do sampled search of array configurations

– Choose array configuration which minimizes performance metric • Performance metric defined as width of

worst-case mainlobe with specified maximum sidelobe

SASS Array Design Criteria

Degrees Beam Pattern: Rectangular Coordinates

Loss

[dB

]

Beam Pattern: Polar Coordinates


SASS Prototype Array Design

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 -0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8 Array Layout

Meters

Met

ers

Antenna Elements (Monopoles)

Ground Plane

• Small enough for transport and able to be mounted on mobile antenna tower – 5’ x 5’ ground plane

• No moving parts, minimize material cost – 8 elements


Modeled SASS Array Response

Mainlobe Characteristics - Max MB = 8º - Azimuth accuracy = 0.16º Assuming 50:1 beamsplit Sidelobe Characteristics - Max SL = -0.2 dB

X [m]

-1 0 1

Y [m

]

-1

-0.5

0

0.5

1Symmetric Array

Mainlobe Characteristics - Max MB = 11º - Azimuth accuracy = 0.22º Assuming 50:1 beamsplit Sidelobe Characteristics - Max SL = -2.5 dB

X [m]

-1 0 1

Y [m

]

-1

-0.5

0

0.5

1SASS Array

Steering Angle [degrees]

High sidelobes

Narrow mainlobe

Modeled Array Beam Patterns

-150 -100 -50 0 50 100 150

-150

-100

-50

0

50

100

150 -10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0 dB

Steering Angle [degrees]

Narrow mainlobe

Low sidelobes

SASS meets 0.4º azimuth requirements and lower sidelobes help reject false target detections

Angl

e [d

egre

es]

Angl

e [d

egre

es]

Modeled Array Beam Patterns


SASS Signal Processing Chain

Digital Signal

Processor

Timing Antenna (x8)

Item Unit Cost Total

Antenna (x8) - Monopole $100 $800

Amplifier - 8-Channel Amplifier $2000 $2000

Receiver (x8) - Ettus N210 Universal Software Defined Radio (USRP) $2200 $17,600

Timing - Trimble Thunderbolt E GPS Receiver $1000 $1000

Timing - Ettus OctoClock-G 8-Channel Clock Distributor $1600 $1600

Digital Signal Processor - Thinkmate Server $10,000 $10,000

$33,000

Simple processing chain and COTS equipment lead to low cost system

Amplifier Receiver (x8)


SASS Sensor Prototype Hardware

Ettus OctoClock-G

Ettus N210 USRPs

Processing Server and Storage RAID

Extra OctoClock-Gs and USRPs for

future 1030 MHz processing

Cost: $33,000 Power Consumption: ~1200W Dimension: ~2’ W x 3’ H (~14U)

Antenna Array


• Overview

• System Design


• Summary

Outline


Hanscom Field Data Collection

Test vehicle with DGPS & transponder

SASS Sensor

MODSEF (1.3 nm away)

Truth sources: DGPS, Lincoln Mode S radar (MODSEF), ADS-B equipped targets of opportunity & video cameras

SASS Sensor Remote

Unit

ADS-B equipped aircraft

DGPS

Transponder Test Vehicle


Hanscom Field Data Collection

SASS Sensor

SASS Sensor Remote

Unit

Phased Array

Phased Array

Cameras

DGPS Base

Station


Flight Facility Tower Cab

• Used to simulate Hanscom (BED) tower – Situation & video displays placed in front of Hut window – Video cameras installed for surveillance verification – Similar view from Hanscom Tower nearby

View of airfield to North from Flight Facility tower cab

Master Processing CPU

Camera Display

Situation Display


Initial Field Experiment

• Mean Error: 22.7 ft • Standard Deviation: 17.2 ft • RMS Error: 28.5 ft

Achieved Accuracy

• Preliminary results are within expected accuracy predicted by model

• Expect improved performance with the addition of a track filter and additional calibration data

0

30

60

90 Feet

Position Error at Hanscom Field

- - - Truth from DGPS

Position Error [ft]

0 50 100 150 200 2500

20

40

60

80Histogram of Position Errors


Aircraft Target of Opportunity


• Overview

• System Design


• Summary

Outline


• Q1 FY16 – Real-time passive geolocation demo

• Finalize USRP real-time interface • Obtain real-time processing rates • Implement single SASS sensor geolocation

• Q2 FY16 – Add 1030 MHz processing for active geolocation

• Detection and demodulation • Interrogation/reply association

– Examine airborne surveillance performance

• Q3 and Q4 FY16 – Field demonstration with passive and active surveillance

Future Work


• SASS provides low-cost secondary surveillance for small airports – Accurate surface surveillance (30ft) and airborne surveillance out to

20nm

• Key benefits – Improved controller traffic situation awareness – Support for automated runway incursion alerting

• Key design features

– Highly accurate, low-cost phased array – Low cost COTS signal processing equipment – State-of-the-art digital signal processing leveraged from DoD work – Low power and small footprint can support mobile applications

Summary


• FAA NextGen Surveillance Branch (ANG-C52) – Andras Kovacs, Matthew Royston, Amit Choudhri, & Rachel Groggel

• MIT Lincoln Laboratory SASS Team – Swaroop Appadwedula, Steve Campbell, Skip Copeland, Bob Downing,

Derek Espinola, Joe Finnivan, Gary Hatke, James Keefe, Jamie Pelagatti, Tom Reardon, Matt Rebholz, Gregg Shoults, Mike Spitalere & Loren Wood

Acknowledgements

small airport surveillance sensor (sass) · small airport surveillance sensor - 4 sdc 18 november...

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