rd9_accelerometer needs for imu - final report 23mar09

Reference: Date: Issue 1

100329339E 25/03/2009 Page i

All rights reserved THALES ALENIA SPACE All rights reserved M032-6

Accelerometer Needs for IMU

ESA contract 21221/07/NL/ST

Final Report

Written by Responsibility/signature

S. Clerc

Verified by

Pierre-Yves Renaud AOCS Department Manager

Approved by

Sébastien CLERC Study manager

Approved by

Stéphane DUSSY ESA Project Manager

Reference: Date: Issue 1

100329339E 25/03/2009 Page ii


CHANGE RECORDS / ENREGISTREMENT DES EVOLUTIONS

ISSUE DATE § CHANGE RECORDS / DESCRIPTION DES EVOLUTIONS

AUTHOR

1 25/03/2009 First Issue S.C.

Accelerometer needs for IMU Doc. Date: 25/03/2009 Page a


TABLE OF CONTENTS 1. Introduction..................................................................................................................... 2

1.1. Purpose................................................................................................................... 2 1.2. References .............................................................................................................. 2

1.2.1. Applicable documents....................................................................................... 2 1.2.2. Reference documents....................................................................................... 2

1.3. Acronyms & abbreviations ....................................................................................... 2 2. Introduction..................................................................................................................... 4

2.1. Background and motivation ..................................................................................... 4 2.2. Presentation of the industrial team........................................................................... 5 2.3. Study logic............................................................................................................... 5

3. Technical requirements and main trade-offs ................................................................... 7 3.1. Accelerometers for orbit control ............................................................................... 7 3.2. Accelerometer needs for aerobraking ...................................................................... 9 3.3. Accelerometer needs for Entry, Descent and Landing (EDL) ................................... 9 3.4. Accelerometer needs for rover navigation.............................................................. 12

4. Synthesis of requirements and identified products........................................................ 15 4.1. Summary of requirements and drivers ................................................................... 15 4.2. Accelerometer classes........................................................................................... 15 4.3. Accelerometer performance requirements............................................................. 17

Measurement range and resolution........................................................................... 17 Bandwidth ................................................................................................................. 17 Noise......................................................................................................................... 18 Bias and bias stability................................................................................................ 18 Scale factor and alignment stability ........................................................................... 18 Interface.................................................................................................................... 18 Mass and power........................................................................................................ 18 Environment requirements ........................................................................................ 18

5. Survey of accelerometer technologies, performances and trends................................. 20 6. Simulation of IMU performances for a landing mission.................................................. 23

6.1. Description of the simulation tool ........................................................................... 23 6.2. Attitude update ...................................................................................................... 23 6.3. Velocity and position update .................................................................................. 24 6.4. Coast phase .......................................................................................................... 24 6.5. EDL ....................................................................................................................... 25

7. Preliminary design of an IMU for space applications..................................................... 28 7.1. MEMS IMU architecture......................................................................................... 28 7.2. Stand alone accelerometer architecture................................................................. 30 7.3. Budgets ................................................................................................................. 30

8. Preliminary development plan....................................................................................... 32 8.1. Products and schedule .......................................................................................... 32 8.2. Accelerometer development activities.................................................................... 32 8.3. IMU development activities.................................................................................... 33 8.4. Stand Alone Accelerometer development activities................................................ 33

9. Conclusion.................................................................................................................... 35

Accelerometer needs for IMU Doc. Date: 25/03/2009 Page 1




1. Introduction 1.1. Purpose

This document presents the main outcomes of the ESA study Accelerometer Needs for IMU performed in the frame of contract 21221/07/NL/ST.

1.2. References 1.2.1. Applicable documents

[AD-1] Statement of Work of Invitation to Tender AO 03.07.2007, ESA/TEC-ECC/4.07

Issue 1. rev. 4, 2007 [AD-2] TAS Proposal, Ref. 8774145, 2007.

1.2.2. Reference documents [RD-1.] Accelerometer Needs for IMU: TN1 IMU and accelerometer needs for space applications,

Issue 3, TAS report n° 100245522W, 2008. [RD-2.] D. Gendre, V. Josselin, S. Dussy, “High-performance accelerometer for on-orbit spacecraft

autonomy”, AIAA 2004-5432, AIAA Guidance, Navigation, and Control Conference and Exhibit, 16 - 19 August 2004, Providence, Rhode Island.

[RD-3.] R.H. Tolson et al., Application of Accelerometer Data to Atmospheric Modeling During Mars Aerobraking Operations, Georgia Institute of Technology, Atlanta, April 2007.

[RD-4.] Lauro Ojeda, Giulio Reina, Daniel Cruz and Johann Borenstein, University of Michigan, “The FLEXnav Precision Dead-reckoning System”, International Journal of Vehicle Autonomous Systems (IJVAS), Special Issue on "Computational Intelligence and Its Applications to Mobile Robots and Autonomous Systems., 4, No. 2-4, 2006, pp. 173-195.

[RD-5.] Durrant, D., Dussy, S., Shackleton, B., and Malvern, A., “MEMS Rate Sensor Becomes a Reality,” AIAA Guidance, Navigation, and Control Conference, AIAA, Hilton Head, NC, 2007.

[RD-6.] P.G. Savage, “Strapdown Inertial Navigation Integration Algorithm Design Part1: Attitude Algorithms”, J. Guidance, Control and Dynamics, 21, 1, 1998.

[RD-7.] P.G. Savage, “Strapdown Inertial Navigation Integration Algorithm Design Part 2: Velocity and Position Algorithms”, J. Guidance, Control and Dynamics, 21, 2, 1998.

1.3. Acronyms & abbreviations

In this document the following acronyms & abbreviations (in addition to standard SI units) are or may be used: AOCS Attitude and Orbit Control System ASIC Application-Specific Integrated Circuit CDR Critical Design Review DM Descent Module EDL Entry, Descent and Landing EIP Entry Interface Point EM Engineering Model FDI Failure Detection and Isolation FOG Fiber Optic Gyroscope



FPGA Field Programmable Gate Array g Earth gravitational acceleration at sea level (9.80665 m/s²) GNC Guidance, Navigation and Control GNSS Global Navigation Satellite System HRG Hemi-spherical Resonating Gyroscope IC Integrated Circuit IMU Inertial Measurement Unit MEMS Micro-Electro-Mechanical System PCB Printed Circuit Board PDR Preliminary Design Review PFM Proto-Flight Model ppm Parties per million (10-6) SOI Silicon On Insulator TRB Technical Review Board VBA Vibrating Beam Accelerometer VHDL Very high speed integrated circuit Hardware Description Language



2. Introduction 2.1. Background and motivation

During the last decade, the European Space Agency has promoted the development of inertial navigation sensors in Europe. This effort has been met with success for the European space industry, both from the point of view of technology and commercially. In the field of gyroscopes, the following sensors have been developed:

− High accuray Fiber Optic Gyros (FOG) (10-3 deg/h class) with applications to Science or Earth Observation missions requiring accurate pointing. This gyro family (Astrix) completed its qualification and will be embarked on Galileo in-orbit validation satellites, Planck, Aeolus, Gaia and Pleiades.

− Medium performance Hemispherical Resonator Gyro (HRG) (0.5 deg/h class) with applications to Telecom missions with not too demanding pointing requirement. The qualification of this gyro (REGYS-20), selected for the geostationary platforms Alphabus and Spacebus 4000, will be completed in 2010.

− Coarse MEMS Rate Sensor covering the low performance needs (5 deg/h class), for all missions requiring rate damping, slew maneuvers, Earth or Sun acquisition, Failure Detection and Identification (FDI), safe mode or coarse navigation functions. The qualification of this gyro, selected for the Earth Observation mission Sentinel-3, will be completed in 2010.

On the other hand, no space qualified European navigation accelerometer exists on the market today, either in stand-alone configuration or integrated in an Inertial Measurement Unit (IMU). This has led the European Space Agency to initiate an accelerometer/IMU development effort. The present study has been the first step in this direction. The development of the European accelerometer/IMU will support the implementation of future European missions involving aerobraking, deep space maneuvers and fine orbit control (for rendezvous, station keeping, coarse formation flying), but most of all landers and rovers. A case in point is the Exomars mission, the first European mission of the Aurora program of robotic exploration. The Aurora missions involve a strong technology development content which can act as building blocks to eventually support human space exploration. Technology demonstration objectives include Entry, Descent and Landing (EDL) of a large payload on the surface of Mars and surface mobility via a Rover having several kilometres of mobility range. In parallel, important scientific objectives will be accomplished through a state-of-the art scientific payload such as the search for traces of past and present life and the characterisation of the water/geochemical environment as a function of depth in the shallow subsurface. Thanks to their low cost and mass, accelerometers could also be used for other applications such as support of spin-stabilized spacecraft or monitoring of flexible modes. Micro Electro Mechanical System (MEMS) technology has been identified early on as a most promising path for a future European space accelerometer, a fact which was confirmed by the present study. Indeed, the technology is now ubiquitous in Earth applications (automotive, mining and petroleum industry, aeronautics, entertainment, medical an military



applications). They cover the whole range of performances, from low-cost coarse inclinometers used in mass market applications to high-end navigation products, with the possible exception of very fine resolution sensors (sub-µg). In terms of MEMS accelerometer technology, pendulum accelerometers with capacitive read-out are the most common. Most of the manufacturing techniques (micromachining, wet or dry etching for silicon) are well mastered by European manufacturers. Some European manufacturers also master Vibrating Beam Accelerometer technology, either with piezoelectric readout (quartz) or capacitive (silicon), mostly devoted to military applications. The present study tried to identify the most promising sensor technologies, as well as the development effort needed to bring a sensor to space qualification.

2.2. Presentation of the industrial team

The present study was managed by Thales Alenia Space France, acting as prime contractor. The technical contribution was focused on the study of accelerometer uses for space applications and the derivation of IMU and accelerometer requirements. In a second phase, Thales Alenia Space France evaluated the expected performances of the proposed IMU for EDL applications through numerical simulation. The development of the simulation tool was supported by the Thales Aerospace division, who brought their knowledge of inertial navigation systems and algorithms. Thales is a major provider of inertial navigation solutions for aeronautics, launchers and military applications. The requirements analysis was supported by Thales Alenia Space Italy. More specifically, the Italian team focused on Entry Descent and Landing, Rover navigation, launchers and science applications, building on the experience of the Exomars mission design, as well as science missions such as GOCE. MEMSCAP studied the existing accelerometer technology, products and manufacturers on the current market and the evolution trends. In a second phase of the study, they proposed a preliminary sizing of a MEMS accelerometer, and helped to define a mathematical model of the sensor. MEMSCAP is a French MEMS manufacturer located in Grenoble, with business units in Norway and in the USA. MEMSCAP products address a large variety of markets, including wireless and optical communications, medical devices, and microphones. MEMSCAP brought to the industrial team their knowledge of both mass market and high-end MEMS products, as well as their mastering of design, production and testing issues. The preliminary design and the development plan of the future IMU was studied by SEA in Bristol, UK. SEA is a provider of advanced technology solutions for space, marine, defense and transportation. More specifically, SEA has a recognized expertise in the development, manufacturing and testing of space electronics. SEA, with the support of AIS, is responsible for the development of the MEMS rate sensor SiREUS.

2.3. Study logic

The study was decomposed into three main phases:

− In a first phase, accelerometer needs for space mission were studied. In parallel, a market and technology survey identified the most adequate products and technology. At the end of this phase, accelerometer products were identified as meeting point(s)



between technology and needs. This phase also identified the most promising technologies, and the crucial design parameters. At the end of this phase, it appeared that a MEMS accelerometer could meet most space applications needs, and in particular EDL, rover navigation, aerobraking and support of chemical propulsion. Silicon vibrating beam and silicon capacitive technologies were considered the most promising.

− A second phase of the study was devoted to the verification of the expected performance of the IMU. A main outcome of this phase was the selection of a candidate gyro to build a future European IMU. Whereas performances for a stand alone accelerometer can be evaluated by simple computations, the end-to-end performance of an IMU during an EDL mission for instance requires a detailed dynamic simulations, taking into account navigation algorithm performance and environmental constraints (mainly thermal). At the end of this phase, it was decided to select the SiREUS MEMS rate sensor as a basis for the preliminary IMU design. Accelerometer technical requirements were consolidated and a specification document was issued.

− The third phase dealt with the preliminary design and development plan. This activity addressed such issues as selection of space-compatible electronics for the MEMS accelerometer, as well as mechanical and electronic design of the IMU, based on the current SiREUS unit. Concerning the development plan, it was decided to focus on the spatialization of a MEMS accelerometer with a good level of maturity rather than starting a new sensor development.



3. Technical requirements and main trade-offs Accelerometers are able to determine the non-gravitational acceleration of a vehicle in a vehicle-fixed frame. In order to be used as an inertial navigation sensor, the accelerometer must be completed by a gyro to recover the attitude of the vehicle in the inertial reference frame, and a gravity model to estimate the gravitational acceleration. For other uses, the accelerometer can be used as a stand-alone sensor. This is the case, for instance, if one wants to monitor a force with a known orientation in the vehicle frame: propulsion monitoring, atmospheric drag for parachute opening and, to a lesser extent, aerobraking. However a low-cost gyro could make an inertial measurement unit more interesting than a stand-alone gyro even in these cases. When estimating the requirements for an inertial navigation system, it is crucial to compare it with alternative navigation solutions. These include GNSS navigation for low Earth Orbit missions, radio-navigation for geostationary or interplanetary missions, and relative navigation sensors (cameras, lidars, radars) for interplanetary approach, landing and rovers as well as rendez-vous and formation flying missions. The benefits of the IMU navigation rely on its relatively low cost and weight, its robustness, while the main drawback is the long term drift due to the double integration needed to determine the position.

3.1. Accelerometers for orbit control

A first type of usage of on-board accelerometers is for propulsive orbit control. More specifically, the following uses can be distinguished:

− Failure detection. A typical case is the detection of a main engine anomaly during a time-critical maneuver such as planetary orbit insertion. A reconfiguration to a back-up propulsion system can be triggered if the anomaly is detected fast enough. Some accelerometer redundancy is required in order to discriminate between propulsion and accelerometer failure. A possible solution consists in placing the three-axis accelerometer set in a skewed configuration with respect to the propulsion axis. Performance requirements are relatively mild in this case, even taking into account large confidence intervals to avoid false alarms.

− Navigation: in this case the accelerometer is used to improve the a posteriori knowledge of the executed ∆V maneuver, which in turns improves the future orbit propagation accuracy. This can be useful for instance for a nadir-pointing orbital mission, to determine more accurately the nadir direction.

− ∆V execution control: in this last case, the propulsion burn is stopped when the commanded ∆V has been reached. This is possible only when the burn lasts (significantly) more than the accelerometer readout period.

Since the acceleration is nearly constant during the ∆V execution, the accelerometer performance requirements for orbit control can be easily analyzed by summing the contribution of the various error sources thanks to a simple spreadsheet, see example in Figure 3-1. The accelerometer characteristics can be optimized so as to meet the requirements for the largest class of maneuvers.



CASE ∆V = 0.1 m/sRequired precision 1.0%confidence interval 3 σResulting precision @ 1 σ 3.33E-04 m/s

Thruster acceleration 0.075 m/s²Manoeuvre time 1.326 sMeas. Frequency 10.0 HzNumber of meas. 14

Error budget measurement error [m/s]

Scale factor 500 ppm 5.00E-05Non-linearity 300 µg/g² 2.22E-05Bias (calibrated) 3.2 µg 4.20E-05Bias drift 45 µg/hr 1.08E-07White noise 20 µg/•Hz 2.26E-04Read out noise 0.06 mm/s 2.24E-04Misalignment 500 µrad 5.00E-05RSS 3.30E-04

contribution

0.0E+00

5.0E-05

1.0E-04

1.5E-04

2.0E-04

2.5E-04

3.0E-04

3.5E-04

Scale

factor

Non-line

arity

Bias (c

alibra

ted)

Bias dr

ift

White no

ise

Read o

ut no

ise

Misalig

nment

Figure 3-1: Example of a measurement error budget for a 0.1 m/s trajectory control maneuver.

When analyzing the requirements for orbit control, the main parameters are the effective acceleration and the length of the burn. Accelerations vary from 0.5 m/s² for a main engine to 0.1 mm/s² for cold gas thrusters or electric propulsion, with a direct impact on the required accelerometer resolution. Longer burns are easier to measure because the measurement noise is filtered over the integration time. The bias stability in itself is never a critical aspect even for very long burns (orbit insertion). On the other hand measuring small accelerations require a careful bias calibration beforehand. The required calibration residual places an indirect requirement on the bias stability.



Low thrust propulsion (electric propulsion and cold gas) is a very specific case. Applications could include fine formation control, autonomous station-keeping for geostationary and Lagrange point missions, and interplanetary cruise. The very low acceleration requires a fine resolution accelerometer, in the µm/s² range. While geostationary station keeping requires a bandwidth of about 1 Hz, interplanetary missions involve very long thrust arcs (10-4 Hz). A multi-mission accelerometer for electric propulsion support should therefore have a measurement bandwidth of at least [10-4: 1] Hz.

3.2. Accelerometer needs for aerobraking

Since the pioneering Magellan aerobraking mission at Venus (1993), the role of accelerometers to support aerobraking operations has steadily increased. Originally seen as an engineering sensor to monitor the structural load on spacecraft surfaces, its role has been extended to autonomous inertial navigation and to the determination of atmospheric properties for science purposes. The recent Mars Reconnaissance Orbiter mission has been equipped with a high-precision accelerometer (resolution of 5 µm/s²), allowing an unprecedented measurement of the atmospheric drag [RD-3.] We have analyzed the performance requirements for an aerobraking mission. For autonomous inertial navigation, a 1 mm/s² resolution seems sufficient, although a general trend toward more autonomy during aerobraking could lead to more demanding requirements in the future. The determination of atmospheric properties (density and wind) on the other hand could in principle benefit from a finer resolution. However the precision of the determination is limited by a number of system-level errors and biases. The first and probably the most important one is the uncertainty on the aerodynamics coefficient database used to recover the density from the drag. The position uncertainty coming from the inertial navigation process has also a strong impact, especially on the recovery of the lateral wind. Finally, structural and slosh modes can induce low frequency disturbances of the measured acceleration which can interfere with the determination of the atmospheric structure. For these reasons, we suspect that in the near future improvements on the determination of atmospheric properties should be obtained by tackling the system-level error sources rather than improving the accelerometer resolution.

3.3. Accelerometer needs for Entry, Descent and Landing (EDL)

The IMUs are widely used in EDL applications for the following purposes

− Inertial Navigation during the Coasting, Entry and initial Descent phases

− Entry Interface Point (EIP) Detection

− Parachute Deployment Trigger detection

− Terrain Based Navigation

A last function, the detection of the touchdown instant, may also rely on specific accelerometers (different from the ones in the navigation IMUs) for some mission scenarios. Inertial Navigation Inertial Navigation is active from the instant of separation until navigation becomes terrain-based (with Doppler radar altimeters –as for the case of ExoMars- or to stereo-



cameras/lidars). The fundamental purposes of the inertial navigation are 1) to propagate the rotational state vector through integration of the gyroscope measurements and 2) propagate the translational state vector through integration of the accelerometer measurements (transformed in the inertial frame through the gyro-based attitude knowledge). Both integration processes have effect on the accuracy at landing: the former process gives the knowledge of the body frame in the inertial frame, the latter determines the knowledge of the local vertical in the inertial frame, their combination identifies the attitude of the descent module in the local vertical frame of the landing site. The inertial navigation error, along with environmental effects, control inaccuracy (reaction control system) and guidance uncertainties contribute to the total attitude error at touch-down. The inertial navigation error allocation in this budget is in turn decomposed into a contribution from gyro and accelerometer errors. Let’s consider first of all the gyroscope requirements determination. The following error contributions can be considered:

− the attitude knowledge error at initialization (i.e. at separation from the Carrier) in [°]

− the residual bias from the calibration in [°/hour]

− the variable drift terms in [°/hour]

− the residual scale factor error around the spin axis in [ppm]

The ability to estimate a constant bias is limited by the variable drift. For a medium accuracy gyroscope with a fixed bias of 1°/hour, the calibration algorithm can be assumed to provide a residual of 10%. (0.1°/hour @ 1 σ). The same value (0.1°/hour @ 1 σ) can be assigned for the contribution of variable drift terms, An attitude knowledge error of 0.1° at separation is a reasonable figure in the ExoMars case. The angular error after three hours of integration reaches 0.44 °@ 1σ. Around the spin axis the error allocation is relaxed to include also the integration of the scale factor error (0.8 °@ 1σ). This figure has been derived fixing a maximum threshold of 0.57°@ 1σ, compatible with the above described error allocation methodology, for the errors allowed around the two axes orthogonal to the spin axis. In turn, a specification for the maximum scale factor error residual is derived. For the case of the ExoMars Descent Module (DM) an error of 6 ppm is determined considering a reference spin rate of 15 °/s. These requirements have been relaxed more recently after evaluation of the relatively contained impact of IMU incremented errors in a simulated environment. Before lander release, radar measurements are rotated in the local vertical local horizontal frame thanks to the inertial attitude integration. A sudden variation of the incremental angle due to the gyro noise coupled with the terrain-based sensor measurement creates a fictitious horizontal velocity error that degrades the attitude profile generation. At lander release this error shall be negligible w.r.t. the noise level in velocity of the terrain-based sensor. This rationale gives a gyro noise requirement of 4 °/√Hz. For the definition of accelerometer requirements we have to consider the following error contributions:

− the error for neglecting the environmental disturbances during the coasting outside the atmosphere (gyro-integration only)

− the error due to the assumption of a flat Mars surface when the navigation changes from inertial to terrain-based

− the error due to accelerometer bias



− the inaccuracy due to the accelerometer scale factor error

− the error in the knowledge of the descent module position at separation from the Carrier

− the error in the knowledge of the descent module velocity at separation from the Carrier

The first and second contributions are one magnitude order lower than the allocation (0.2 °@ 1 σ) and in practice negligible. The bias and scale factor errors have a large contribution on the final accuracy of the local vertical knowledge. The determination of this impact has been studied by a parametric study of the final angular displacement after integration of the trajectory. Over the Entry phase, the accumulation of angular displacement due to a scale factor error in the order of 300 ppm and a bias in the order of 0.3 mg yields a 0.1° error. The allocation of the Position Error and Velocity Error in the knowledge of the DM at separation is consistent with the overall budget and the technological limits of the state reconstruction techniques from ground.

Planar Angle Error

-0,5

-0,4

-0,3

-0,2

-0,1

0

0,1

0,2

0,3

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0,5

0 50 100 150 200 250 300 350

Time [s]

Erro

r [de

g]

err acc+err acc-err acc+,fpa+err acc+,fpa-err acc-,fpa+err acc-,fpa-

Main Parachute Retrorockets Firing

Figure 3-2: Evolution of the planar angle related to the accelerometer error, from EIP to landing

point. Cases of positive or negative bias and scale factor are represented by the blue and magenta curves respectively. Error evolutions are only slightly impacted by the gyro error of

±0.2 deg.

EIP detection While the entry phase, thanks to its short duration, does not seem to impose a stringent accelerometer calibration, the same doesn’t apply to the EIP detection. Analyses show that:

− Calibration of bias around X axis before separation (handled by the Carrier/Mission Control Center) shall be guaranteed with a residual error of 10% of the nominal bias

− If necessary, the descent module GNC shall be able to improve this result with a further reduction of the residual to 2÷3%

As far as the accelerometer noise is concerned, the most demanding algorithm is again EIP detection. In this algorithm we must identify the instant when a specific load factor threshold is encountered, typically 1.5 e-3 m/s². The noise must be therefore filtered to be sufficiently lower than this threshold. A filtering time of 5 s is consistent with an altitude range over the Mars surface between 100 and 120 km. Finally, an Accelerometer Noise better than about 0.1 mg/√Hz and a Quantization Noise better than 600 µg @ 100 Hz are required.



Parachute Deployment Trigger detection The sensitivity of two candidate algorithms has been analyzed: 1) a time-tagged propagation derived from two time evaluations along the Entry acceleration time history (Time Tagged criterion); 2) direct measurement of the acceleration in proximity of the opening point (g-switch criterion). Combining those algorithms allows a reliable determination of the parachute opening point. Sensor errors can be split in two categories:

− errors mainly influencing the mean of the Mach number, the dynamic pressure and the altitude errors (i.e. sensor bias error and scale factor error)

− errors mainly influencing the standard deviation of the Mach number, the dynamic pressure and the altitude errors (white noise error and quantization error)

Results demonstrated that both algorithms are quite insensitive to these sensor errors. Furthermore, the sensitivity curves show a quite flat trend for errors between 1 and 4 times the figures specified by the other mission needs: therefore parachute deployment trigger algorithms are not important drivers for the choice of the accelerometers in the frame of EDL applications. Terrain Based Navigation Terrain Based Navigation uses the IMU to complement the measurements for terrain approach and landing. This auxiliary contribution to the navigation is two-fold. The rotational state estimation, fed by gyroscopes, is used to control the attitude in the landing terrain reference frame. The accelerometer measurements are fused with the measurements of the terrain-based sensors for the descent and horizontal translational navigation and compensate the delays of the terrain-based sensors. This phase is not a main driver for the selection of the IMU since this unit is not the main sensor any longer.

3.4. Accelerometer needs for rover navigation

Utilisation of the IMU in the Rover GNC The determination of the state vector in most rover exploits largely the so-called visual odometry, a process of stereoscopic elaboration of the images in successive steps that permits determination of depth of specific reference “features” and evaluation of the motion with respect to them. However the IMU plays an important role in the rover navigation. With respect to other rover sensors (mainly encoders connected to the wheels, Sun sensors or star trackers and cameras) IMU sensors have the advantage to give absolute measurements in an inertial reference frame but the drawback of the slow drift in the estimated states due to the presence of biases requiring periodic reset. The following main functions can be envisaged for utilisation of the IMU in the Rover GNC:

− Determination of Roll and Pitch

− Fixing of Azimuth

− Propagation of Azimuth

− Wheel slippage evaluation

Determination of Roll and Pitch Determination of roll and pitch angles strongly relies on the IMU information. If the rover is still, the accelerometers measure the components of the gravity vector in the axis normal to the chassis plane. From these measurements it is immediate to determine the roll and pitch



angles. If the rover is moving, the gyros can be used to integrate the initial roll and pitch fixed angles. If the rover is operated with sequences of moving and rest periods, the IMU platform is able to guarantee a good propagation of the roll and pitch angles even in presence of quite large drifts. A heuristic approach can be used to combine the accelerometer and gyroscope measurements depending on the status of the rover in order to get the best accuracy [RD-4.]

XNominal

YNominal

ZActual ZNominal

eroll eyaw

XActual

epitch

YActual θSun

Figure 3-3: Identification of the azimuth (yaw) error.

Fixing of Azimuth: Sun sensor and accelerometer data fusion A Sun sensor is used to fix the heading by processing the sensor measurements with the information of Sun ephemeredes, rover location (latitude and longitude on the planet), and knowledge of the body vertical axis (as described in the previous paragraph). The heading error augments with the inverse of the declination of the Sun (see Figure 3-3). For instance, a minimum declination of 10° implies an amplification of the error of 5.7. To obtain a 0.5° heading angle error, the maximum error for each axis of the accelerometer shall be of the order of 0.3 mg. This constraint corresponds to a sizing figure for a number of accelerometer error sources.

− Bias, bias stability and noise < 0.1 mg (each)

− Misalignment < 0.03 deg

− Scale Factor < 100 ppm

where the values for the systematic errors have to be understood as residuals of the in-line calibration processes. Propagation of Azimuth: Encoder and gyro measurements fusion The azimuth angle evolution is related to the differential velocity of the wheels on the right and left side of the vehicle. Exploiting this concept it is possible to build a Kalman filter fed from the odometric and gyro measurements. Three problems must be solved:

− A periodic fixing is necessary as put in evidence in the previous point

− Yaw propagation is mainly affected by the gyro drift so that periodic calibration is necessary

− Actual encoders information are affected by slippage that must be purged out through non-trivial algorithms



Wheel slippage evaluation An IMU-based principle for slippage detection criterion consists in comparing encoder outputs with outputs from an accelerometer mounted in longitudinal direction. Maximum longitudinal acceleration for a current rover is in the order of few tens of mm/s2. To detect perturbations in the longitudinal acceleration or braking phases due to slippage a resolution of few mm/s2 is needed. This is in general a very stringent requirement for the light and small accelerometers used in the rover applications. Other strategies based on inclinometers, steering potentiometers and rocker-boogie potentiometers for the slippage detection are generally preferable.



4. Synthesis of requirements and identified products 4.1. Summary of requirements and drivers

Table 4-2 summarizes the main drivers and requirements for space applications of accelerometers.

4.2. Accelerometer classes

The mission requirements have been gathered to define three accelerometer classes:

− A specific accelerometer for launcher applications. This accelerometer will be tailored to measure high accelerations with a very different environment than space missions (high vibration, low radiation, short lifetime), and specific constraints in terms of cost and availability. For these reasons, it is considered that the launcher-oriented accelerometer would not be similar to the accelerometer for space missions.

− A high-resolution accelerometer for micro-propulsion applications (electric and cold gas propulsion). A sub-µg resolution is required, which cannot be met with current MEMS technology. An accelerometer based on electrostatic suspension could be used for this application, see [RD-2.]

− Finally, a generic accelerometer covering most space applications. The corresponding requirements are detailed in the next section.

The potential market for each accelerometer has been studied, based on planned ESA missions in the next decade. The reduced number of units would justify a relatively high recurrent price.

Application Coarse Medium High Science grade

Geostationary 200 D (main engine) C (SKM)Lagrange points 3 C (SKM)Interplanetary mission 4 A (FDIR) B (TCM) C (TCM)w/ Aerobraking 1 A Fine Orbit Control / RdV 3 C (chemical) D (µ-prop.)Launcher 150 APassive Landing 5 A (parachute)Controlled Landing 1 A Rover 1 A (local vertical) B (wheel slippage)Drag-Free 3 AFormation flying 3 C (deployment) D (position control)Electric Propulsion 1 D

Number of missions

A mandatory (only possible solution)B useful (probably the best solution)C possible (balanced trade-off)D unlikely (probably not the best solution) no use

Table 4-1: Synthesis of the foreseen accelerometer and IMU needs for the 2015-2025 time frame.

Accelerometer precision ranges from coarse (0.1 mg) to Science grade (better than 10-9 g).



Missions Applications Range Precision Drivers

Launcher GTO 100 m/s² 1 mm/s² Cost, availability Very good linearity (< 100 µg/g²) Lifetime/radiation less important

Main engine FDIR 500 mm/s² 8 mm/s² Robustness/reliability ∆V 0.1-10 m/s 30 mm/s² 0.1 mm/s² Low noise (read out < 0.09 mm/s²) Fine orbit control (1 mm/s) 30 mm/s² 0.1 mm/s² Very low noise ( white < 10 µg/•Hz,

read out < 0.01 mm/s²) Propulsive maneuvers

GEO Station keeping (10 mm/s)

10 mm/s² 0.1 mm/s² Low noise (read out < 0.09 mm/s²) Bias stability (< 3 µg/hr) Cost, availability

Navigation 6 mm/s² 0.5 mm/s² Low noise inertial navigation algorithm

Aerobraking Atmosphere reconstruction (science)

6 mm/s² 50 µm/s² Very low noise (read out < 0.05 mm/s²) Navigation algorithm design Fusion with thermal sensors

Inertial navigation 100 m/s² 0.5 mm/s²

Bias stability (thermal drift < 20 µg/°C) Robustness Mass/power Gyro quality (< 1°/h) and navigation algorithm key drivers

Entry detection 1 mm/s² 0.5 mm/s² Bias stability (thermal drift) Mass/power

Parachute deployment 10 m/s² 7 mm/s²

Bias stability (thermal drift < 15 µg/°C) Scale factor stability (< 300 ppm)

EDL

Airbag venting 400 m/s² 1 mm/s² Low cost/mass Robustness High bandwidth (> 500 Hz)

Navigation/roll pitch 4 m/s² 4 mm/s² Low power/mass Bias stability (< 100 µg/hr)

Navigation/azimuth 4 m/s² 3 mm/s² Low power/mass Rover

Wheel slippage detection 10 mm/s² 0.5 mm/s² Low noise

Alignment stability (<150 µrad)

Formation Flying Fine position control 1 mm/s² 1 µm/s²

Very fine resolution Bandwidth > 0.5 Hz Low mass/power

GEO station keeping 5 mm/s² 0.5 µm/s²

Very fine resolution Low mass/power Cost, availability Electric

propulsion Interplanetary cruise 5 mm/s² 1 µm/s² Very fine resolution

High bias stability (> 2 hours)

Table 4-2: Main drivers for accelerometer applications



4.3. Accelerometer performance requirements

The specified performance requirements are summarized in Table 4-3 below and detailed in this section. Parameter Value Unit Comment Driverrange 20 g i.e. ±20 m/s at 10 Hz EDLacquisition rate 10 Hz settable ; goal: up to 100 Hz 100 Hz for EDLbias 300 mg will be calibratedbias stability 1 hour 45 µg with 3°C temp change TCM 1 m/sbias stability 90 s 3 µg with ±3°C/hr temp change calibration, TCM 1 m/sbias stability 200 s 1 mg with ±60°C temp change Entrywhite noise 20 µg/•Hz TCM 1 m/s, entry detectionScale Factor 500 ppm parachute openingAlignment 300 µradNon-linearity 400 µg/g² i.e. 0.8% full range SF error EDLread out noise 0.06 mm/s i.e. LSB < •12 * 0.1 = 0.21 mm/s TCM 1 m/s, Aerobraking

Table 4-3: Characteristics of Accelerometer / IMU for generic space applications.

Measurement range and resolution In terms of measurement range and resolution, the EDL application appears as a specific case, requiring a measurement range of 20 Earth g’s, and relatively coarse resolution. Most other space applications would be covered with 1 g range sensor and a resolution of 0.6 mm/s². The technology survey (see chapter 5. ) indicated that the sensor intrinsic errors of a 20 g sensor could be compatible with the precision requirements for the 1 g applications. This is especially clear for the VBA technology whose performances are relatively independent of the measurement range. Nevertheless, the resolution of the accelerometer could be limited by the quantization error. A ±20 g range leads to a LSB of 610 µg (6 mm/s²) for 16 bits quantization. The resulting quantization error is equivalent to 0.2 mm/s at 10 Hz, which is too high to monitor small thruster pulses or perform navigation during aerobraking. A reduction of the scale factor gain (by a factor of 4 or more) would bring the LSB to the expected value. It is therefore thought that the same sensor can meet all the requirements thanks to a limited modification of the readout electronics. Alternatively the use of a higher bit depth, if possible, would solve the problem. Also note that the full range (±20 g) is required for EDL applications at 100 Hz, while the 0.6 mm/s² requirement for other applications holds at 10 Hz. Bandwidth Most AOCS applications run at a relatively low frequency (8-10 Hz). However simulations showed that for EDL, some improvement could be gained by performing navigation at a higher rate (50 to 100 Hz, see chapter 6. ) This is especially true for the gyro measurements, but the same output rate should be used for gyro and accelerometer measurements. On the other hand measurements of a constant low thrust could benefit from a lower rate to limit the impact of the readout noise. As a goal, a settable measurement frequency in the range [2 ÷100] Hz (bandwidth 1÷50 Hz) is therefore specified.



Noise White noise and quantization error dominates the budget for the measurement of small thruster pulses (typically 0.1 m/s). A value of 20 µg/√Hz is specified (63 µg rms at 10 Hz). Bias and bias stability A first important remark is that the absolute value of the bias is never an issue for space applications because bias calibration is almost always possible before the measurement begins. This is a major difference with Earth applications were calibration is more delicate or impossible. An exception is of course rover navigation applications which involve a more intricate calibration procedure using sensor fusion, see section 3.4. On the other hand a particular care should be devoted to the bias stability when designing the sensor. As mentioned earlier, the bias in itself does not have a direct impact because of the relatively short integration times of space applications (a few minutes at most). The indirect effect of limiting the reachable calibration residual on the other hand is critical. Based on typical accelerometer characteristics, we have estimated that the optimal calibration time to reach a given calibration residual. This requirement is naturally expressed as a maximum Allan deviation of 30 µm/s² over a 90 s horizon. This requirement shall hold against typical temperature variations of ±3 °C/hr. Scale factor and alignment stability A scale factor error of 500 ppm and an alignment stability of 500 µrad (at unit level) are specified. The full range scale factor error may affect the navigation for EDL applications around the peak deceleration point. A maximum error of 0.8% can be tolerated. Interface In term of interfaces, a RS422 bus is considered as a primary target for an IMU. Mass is indeed a strong driver for missions considered here (mostly interplanetary missions), while the exchange data rate will remain low. Mass and power For a stand-alone accelerometer axis, the mass of the sensor is expected to be lower than 50 g and the power input limited to 0.5 W. Environment requirements The environment is specified Table 4-4 below. Shock survival could be an issue for some detector design. The operating temperature range requirement would probably necessitate a temperature calibration process.



Parameter Value Unit Comment Drivermass 50 gpower 0.5 Wdiameter 25 mmMin Op Temp -20 °C Rover, LandingMax Op Temp 65 °C LandingMin Non-Op Temp -30 °CMax Non-Op Temp 65 °Cpressure 0-1100 mbarSinusoidal vibration ± 10 mm 5÷20 Hz Launch

20 g 20÷100 HzRandom vibration 3 db/octave 20÷100 Hz

1 g²/Hz 100÷2000 HzShock 1000 g 1500 Hz half-sine PyroRadiation 100 Krad total dose full performance interplanetary missions

Table 4-4: Desired system and environment characteristics for the accelerometer



5. Survey of accelerometer technologies, performances and trends

A survey of existing accelerometer technologies has been performed and the best candidates for space applications have been identified. The main findings are summarized in Table 5-1 and detailed hereafter. The best performance is obtained with Vibrating Beam Accelerometers made in Quartz. They are considered as high end MEMS components to be used in navigation systems for civil and military avionics and for ammunitions guidance (missiles for instance). Only a few providers are making these units (among others Safran and Thales Avionics in France, former LITEF in Germany) and they are usually vertically integrated. As they are quite costly and are parts of strategic systems, the devices are usually sold in Inertial Measurement Units and/or full Inertial Navigation Systems, not as stand-alone components for custom integration. These devices are commonly known as the best choice for long term stability of the performances (bias drift, scale factor drift), low thermal dependency (due to the material itself but also due to the decades of efforts spent to optimize their assembly lines and materials). Technically-wise, they are obviously the less risky solution for the 0.1mg range required by the space applications. Built out of Quartz, they benefit from the piezoelectric effect which simplifies the electronics read-out circuitry (shift of resonant frequency with acceleration load). Manufactured in low volumes, they are quite expensive to manufacture and do not exist in single chip three axis versions (technology limitations). Some improvements are in the research phase using Deep Reactive Ion Etching for Quartz. One can expect that either performance will improve or that the number of players in the field will increase and drive the costs lower. Two other alternative approaches to Vibrating Beam Accelerometers made of Quartz can be foreseen as potentially suitable to reach the medium quality requirements for Space applications:

− Vibrating Beam Accelerometers (VBA) based on single crystal Silicon

− Variable capacitance accelerometers based on either Bulk Micromachining or Silicon on Insulator (SOI) technologies.

VBAs on Silicon are based on the same principle than VBAs in Quartz but use a capacitive detection scheme rather than the piezoelectric effect of Quartz. Implementing VBAs in Silicon would require expertise in the electronics field similar than for state-of-the-art MEMS gyros. The drive and detection schemes are very similar and European expertise in the field of MEMS gyros could be leveraged to develop this technology. State-of-the-art variable capacitance accelerometers (based on bulk or SOI) are today mainly used for cost driven high volume market places (low performance). Most European companies using that technology are addressing the consumer and automotive markets (e.g. ST Microlectronics, VTI Hamlin, German companies) and very few companies in Europe are committed to the navigation market place (mainly Colibrys, MEMSCAP). Current performance is today in the mg range. There are no obvious limitations from the technology point of view (Single crystal Silicon) and probably gaining an order of magnitude is possible with careful design of the accelerometer component (MEMS + ASIC + Packaging) at the cost of a higher technical risk than for a Quartz VBA but with probably decent costs reductions.



Nevertheless, for a given IC architecture for capacitive detection, it is possible to evaluate bias drifts only arising from the IC. This should give us a first limiting factor for this type of devices. For instance, let’s consider two options:

− Open loop with sigma-delta signal conversion

− Closed loop with sigma-delta signal conversion.

Both systems require a Voltage reference (Vref) as stable as possible. In the case of an open loop architecture, the signal is proportional to Delta Capacitance times Vref. It is possible to get rid of any fluctuation of Vref by carefully choosing the output signal formulation. The drift would then mainly come from the charge migrations in the circuitry, and hence an excellent bias stability is expected. In the case of a closed loop system, the output signal is proportional to Vref squared. The best commonly available voltage sources today have variations of 5 ppm/°C. Since the output signal is proportional to the square of Vref, this would lead to 10 ppm/°C variations for the bias values.



QuartzVBA Silicon VBA Capacitive SOI Capacitive

Bulk Material

Quartz Single crystal Silicon

Single crystal SOI

Single crystal Silicon

Sensor die design complexity

- - Resonant , cross

talk due to asymmetries

- - Resonant device

+ Cross-talk

+ Cross-talk

Sensor die volume

= Typically 5×5 mm²

= = =

Manufacturing complexity

- Typically wet etch control is critical

(time etch)

- Side walls etch control critical

+ Aspect ratio and trench quality are

critical

+ Typically 3 wafer stack, wafer to

wafer alignment is critical

Packaging volume

= Typically ceramics

= = Typically ceramics

= Typically ceramics

or TO cans IC volume

+ -

- max 15mm2

- max 15mm2

IC Complexity

- - - Resonant type of device, feedback

loop needed

- - - Resonant type of device, feedback

loop needed

- Delta-Sigma with pF

values

- Delta-Sigma with pF

values

Thermal sensitivity

-

Unknown +

+ Stack of wafers

Shock resistance

- Quartz

+ Buckling

acceleration

++ Single wafer but

overloads difficult

+ Stack of wafers but overloads available

Noise

+ Operates under vacuum, noise

mainly from electronics

=

= Small mass,

Requires reduced pressure in the

MEMS die cavity

= Large mass

Bias stability

= = Voltage reference in

closed loop configuration

= Charging effect,

voltage reference in closed loop

configuration

= Charging effect,

voltage reference in closed loop

configuration Scale Factor Stability

++ = Mainly IC design

dependent

- IC design

- IC design

Yield - - - - + - Costs - = + +

Table 5-1: Comparison table between MEMS technologies for accelerometers



6. Simulation of IMU performances for a landing mission 6.1. Description of the simulation tool

The performance of the IMU and associated inertial navigation algorithms was investigated by simulation. The high-fidelity “Safe-to-Mars” software was used to generate 6-degree-of-freedom trajectories representative of a Martian landing mission. This software uses the EMCD atmosphere model, a reference aerodynamic database, a J2 gravity model and a specific model of parachute opening. The trajectories are sampled at 1 kHz. They are used to feed the Real-World angular and linear accelerations to the sensor models and as reference to compute the navigation error. A fixed offset between the IMU and the lander center-of-mass can be specified. Finally, the Real-World model includes a user-provided temperature profile during the EDL timeline. The gyro model used for these simulations is a high-fidelity model of the SiREUS. This model includes a noise shaping filter to reproduce the sensor power spectrum density (PSD) and an ad-hoc statistical model of the temperature sensitivity of the bias. A constant scale factor error and quantization effects are also taken into account. The accelerometer model on the other hand is a generic mathematical model including white noise, scale factor and non-linearity errors, quantization errors. The accelerometer bias is assumed to be calibrated at entry. Bias drift is taken into account as a random linear function of both time and temperature.

6.2. Attitude update

The inertial navigation algorithm relies on first an integration of the measured angular rate in order to determine the attitude quaternion, thanks to the following equation

,0

21 qq ∗

=

ω& , (1)

where (0, ω) denotes the angular rate seen as a pure quaternion and ∗ is the quaternion product. High-rate gyro measurements are integrated over the AOCS period to get a rotation vector Φ:

.1

∑+

=Φn

n

t

ti tδω (2)

Let φ denotes the norm of the 3-dimensional vector Φ. Then the quaternion is updated with the integration scheme

( )( )

nn qq ∗

Φ=+

φφ

φ

2sin

2cos1 . (3)

This scheme is exact whenever the direction of the angular rate vector ω remains constant during the integration time. If this is not the case, an integration error is introduced: the so-called “coning” error, see [RD-6.] In practice, the impact of this error depends on the high frequency vibration environment of the sensor. This environment is not faithfully reproduced by our simulator so the importance of coning cannot be directly investigated. Nevertheless, one can get an idea of this impact by looking at the integration error introduced on the 1 kHz-sampled trajectories. In fact, even a 1 kHz integration of equation (3) yields a small error (typically 0.01°) with respect to the higher-order reference simulation. This error increases with the AOCS integration period. With a 10 Hz integration rate more representative of flight



GNC software, the error reaches 0.06°. This error can be reduced by using a coning compensation algorithm4. For instance, one can replace equation (2) by equation

.211

∑+

×Φ+=Φ

n

n

t

tiii tδωω (4)

It can indeed be shown that equation (4) is equivalent to equation (1) up to second order in time. But equation (4) is much simpler than (1) and can therefore be integrated at high rate. In practice, integration of equation (4) at 1 kHz combined with quaternion update (3) at 10 Hz is equivalent to quaternion integration at 1 kHz with a much reduced computational throughput. Although the coning compensation algorithm was shown to efficiently reduce the integration error, it was not deemed useful for current EDL applications. Indeed the error introduced by the sensor is two orders of magnitude larger than the integration error, making the latter in practice negligible. Therefore the coning compensation algorithm has not been considered in the rest of the study. Similarly, integration errors arise for velocity and position update, referred to as sculling and scrolling errors, see [RD-7.] These errors are even more negligible with respect to IMU errors for current EDL applications. Sculling and scrolling compensation algorithms have therefore not been considered.

6.3. Velocity and position update

The velocity is updated by integrating accelerometer measurements and the adding gravitational acceleration term. The attitude quaternion is used to perform the update in the reference inertial frame. A second order algorithm uses the half-sum of the attitudes at time time tn and tn+1:

.~~21 11

11

∗

∗+∗

∗= ++ ∫∫

++

nt

t

nnt

t

n qdtqqdtqn

n

n

n

aaA (5)

The velocity update reads:

( ) .1

1 ∫+

×+++=+

n

n

t

t

ngrav

nn dtt dxFAvv ωδ

The gravitational acceleration Fgrav is computed at time tn. The last term is the compensation of the lever-arm d between the sensor and the body center-of-mass. Finally, the position is updated thanks to second-order half-sum velocity integration:

( ) .21 11 tnnnn δ++ ++= vvxx

6.4. Coast phase

The IMU-based inertial navigation starts after separation from the carrier module. During the coast phase outside the planetary atmosphere, attitude is updated from gyro measurements while non-gravitational acceleration is essentially zero. The length of the coast phase can be longer than the EDL phase itself, as is the case for the Exomars mission. The coast phase will therefore account for a significant part of the inertial navigation error, especially as far as attitude is concerned. Because of the relatively large spin rate, the gyro scale factor error can have catastrophic consequences on the attitude around the spin axis. A scale factor error of 0.4% results in 11° of error after 30 minutes of coast. Note that the inertial direction of this



axis during cruise is almost normal to the local vertical at the landing point, so the coast phase attitude error directly impacts the knowledge of the local vertical at touch-down. On the other hand, the spinning motion reduces the impact of biases around transverse axes. A typical error of 1° around transverse axes arises from the misalignment error, but this error does not grow with time, A calibration of these terms is not required. To asses the impact of the coast phase, we have simulated a 2 hour phase with a constant spin rate of 15°/s. The scale factor is calibrated during the first 20 minutes of the simulation. The results are displayed on Figure 6-1 show that the error remains below 2° after one hour.

Figure 6-1: MEMS rate sensor integration error during coast phase.

Left and right: two different random seeds.

6.5. EDL

The coast phase final attitude error is used to initialize the EDL simulation. The attitude error increases during the entry because of the nutation induced by aerodynamic forces. At the end of the entry phase the parachute is opened. A verticalization of the trajectory occurs and the error along the spin axis is transferred to transverse axes. Results shown in Figure 6-2 show a resulting attitude error of approximately 5°. This figure is deemed compatible with the touch-down requirements. The velocity and position error are displayed in Figure 6-3. As expected, neither the lateral velocity nor altitude can be predicted accurately enough to initial and control the powered descent phase. Additional sensors are required such as a radar altimeter, a Doppler velocimeter, or a vision-based system. Finally, we show in Figure 6-4 the evolution of the error on the knowledge of the local vertical. The figure also shows the relatively small contribution of the position error to this value. These preliminary results seem to indicate that an Inertial Measurement Unit based on the SiREUS MEMS rate sensor could be compatible with a landing mission with a 5° requirement on the local vertical at touch-down.



Figure 6-2: SiREUS MEMS rate sensor integration error during EDL.

Left and right: two different random seeds.

Figure 6-3: Position error during EDL: SiREUS MEMS rate sensor combined with model of

future European accelerometer. Left and right: two different random cases.



Figure 6-4: Evolution of the error on local vertical during EDL: SiREUS MEMS rate sensor

combined with model of future European accelerometer. Left and right: two different random cases.



7. Preliminary design of an IMU for space applications 7.1. MEMS IMU architecture

The reference rate sensor for this activity was selected to be the European MEMS rate sensor SiREUS [RD-5.] The reference accelerometer was the capacitive MEMS technology which, as discussed above, has been assessed to provide a suitable level of performance compared to the Technical Requirements presented in chapter 3. Experience from the MEMS rate sensor development highlights a number of key factors in achieving the best possible performance from this technology, which can be brought to bear in the foreseen accelerometer development. In particular it is evident that MEMS technology there is a very strong interaction between the detector, the proximity electronics and the related control loops that must be optimized to achieve a good level of performance. This is balanced by the ever-present constraints of availability of space components, in particular following the SiREUS approach of using ITAR-free parts.

The following design drivers were therefore considered in the derivation of the design:

− Meeting key performance parameters discussed above.

− Matching accelerometer proximity electronics as close a possible to the host (SiREUS) architecture and component selection; minimizing component cost and integration cost.

− Mechanical integration of the accelerometer detectors and support electronics with a minimal impact on the unit mass/power/volume characteristic.

− Integration of accelerometers within requirements for misalignment (absolute and stability).

An outline of the IMU Electrical Architecture is shown in Figure 7-1. The majority of the accelerometer functionality is provided by an extension of the host unit; in this case SiREUS. This provides:

− Telecommand and Telemetry Support − Secondary Power

The detector baseline is a pendulum style capacitive MEMS accelerometer as discussed above and accelerometer detectors are accommodated on a single printed circuit board (PCB) with their associated proximity electronics. In order to not introduce new component types which can increase unit costs (MOQs, parts qualification costs, etc) an initial proximity electronics design has been derived using the same component types present in the SiREUS parts list. This approach includes the same electrical architecture as the SiREUS unit using lower cost sample & hold circuits to minimize the use of more expensive Digital-to-Analogue Converters (DACs). An assessment of this approach confirms operation is feasible up to 100 kHz for detector drive and sense circuits.



Figure 7-1: Outline of the IMU electrical architecture.

Figure 7-2: Outline of the IMU mechanical architecture



The remainder of the accelerometer functionality is integrated into the existing SiREUS FPGA design. Here VHDL IP CORES already developed are used to interface to the proximity electronics ADCs and DACs. Similarly a sub-set of the rate sensor processing IP COREs can be used to perform the key accelerometer functions of synchronous demodulation, filtering and frequency decimation to provide the accelerometer outputs in the required bandwidths. An initial sizing indicates that the required accelerometer functions can be readily accommodated in the FPGA within the current spare 50% of the capacity of the Actel RTAX2000 device. As for the current SiREUS development it is understood that the FGPA design would requires migration to a European ASIC as a final step to support a fully ITAR free status.

For the mechanical integration consideration again maximum experience has been derived from the SiREUS development in the accommodation and management of a similar class of detector. The preliminary approach is outlined in Figure 7-2.

7.2. Stand alone accelerometer architecture

A proposed tri-axis accelerometer architecture is described in Figure 7-3. A single axis configuration could also be envisaged. The support electronics could also be hosted in a separate processing unit.

Figure 7-3: Tri-axis stand-alone accelerometer architecture.

7.3. Budgets

From this preliminary design activity a comparison table of the impact of integrating the accelerometer functions is indicated in Table 7-1. For the Stand-Alone accelerometer, the estimation depends on the choice between a discrete electronics FPGA and a mixed signal ASIC. Predicted values are indicated in Table 7-2, based on a tri-axis accelerometer design.



Parameter Predicted IMU Value

Actual SiREUS Value

Requirement Estimate

Power < 5.5 W @ 28Vdc

< 5.2 W @ 28Vdc < 0.5W / axis

Accelerometer PCB + FPGA delta approx 300 mW = 100 mW/axis

Mass < 750 g 750 g < 50 g / axis Accelerometer PCB (ignores FPGA) approx 60 g = 20 g/axis

Volume 100*100*90 mm

110*110*70 mm < 25 mm /axis

Accelerometer PCB (ignores FPGA) Approx 70 * 70 mm = 40 * 40 mm /axis

Table 7-1: Budget Comparison for Accelerometer Integration

Parameter Predicted Stand Alone Value Estimate

Power Mass

<1.6 W @ +/- 5Vdc < 158 g

Accelerometer PCB = 100 mW/60g

CSI PCB = 1500 mW/48g Mechanical and misc = 50 g

Volume 90*90*35 mm Two PCB module Power Mass

<0.9 W @ +/- 5Vdc 60 g

Accelerometer & ASIC PCB = 100 mW/60g

Volume 90*90*35 mm One PCB module

Table 7-2: Predicted Stand Alone Accelerometer Budgets. Top rows: discrete electronics FPGA, Bottom rows: Mixed Signal ASIC.



8. Preliminary development plan 8.1. Products and schedule

A development plan for a future space accelerometer is proposed, addressing both integration inside the MEMS rate sensor to create an IMU and the development of a stand alone version. Three product lines are identified:

− The accelerometer detector

− The stand-alone accelerometer (SAA) with supporting electronics and packaging

− The MEMS IMU

A three-phase development plan is proposed (see Figure 8-1):

− Phase 1 (6 months) for the development of the concept. A key point during this phase is to select the most promising detector, taking into account the constraints at IMU and stand alone design level. A certain level of risk (in terms of schedule) is associated to this activity, related to the consistency of the detector characteristics with performance requirements and environment constraints. This phase ends at Preliminary Design Review (PDR) of all three products.

− Phase 2 (6 months) for the development of the Engineering Model (EM). This phase ends with the Critical Design Review of the SAA and IMU, and the Technical Review Board (TRB) at accelerometer detector level, analyzing the results of the detector characterization campaign.

− Phase 3 (6 months) for the development of the Proto-Flight Model (PFM), and the evaluation of the manufactured detector.

8.2. Accelerometer development activities

As far the detector is concerned, a first key point concerns the early concept demonstration. This demonstration relies on performance characterization by trials on critical requirements if necessary, but also on assessment of the choice of materials and processes, in particular with respect to the foreseen radiation environment. This point shall be studied at a theoretical level at this stage. Packaging issues for the Flight Model shall be addressed. The detector characterization activities will include further performance assessment, structural and radiation testing if required. Finally a batch evaluation plan could follow the outline established for the development of the MEMS rate sensor.



Figure 8-1: Proposed development plan.

8.3. IMU development activities

In the first phase, the proximity electronics for the accelerometer support and the VHDL functions to be implemented on the FPGA will be designed. After PDR, the accelerometer support PCB will be designed and developed. This phase will also address the thermal and structural design modifications required on the IMU to integrate the accelerometer PCB. The IMU EM would allow a (limited) environmental testing and perhaps an early in-flight test. The PFM will then be designed and qualified. The unit would be available for third party testing and/or an experimental flight opportunity. Note that the most likely opportunity would be to monitor spacecraft propulsion on a LEO or GEO spacecraft.

8.4. Stand Alone Accelerometer development activities

The design of the SAA product would rely on the outcome of other activities:

− Selected detector

− Proximity electronics PCB developed for the IMU

− FPGA control electronics derived from the IMU design



The Engineering Model could as previously be used for limited environmental or third party testing. The design of the SAA Flight Model should decide between discrete electronics or ASIC for support functions.



9. Conclusion The present study has analyzed the needs for an accelerometer specifically designed for space applications. A range of 1g and a resolution of the order of 50 µg is required to cover most applications except landing missions, which need a wider range of 20g and a resolution of 1 mg. It is thought that a single sensor possibly with different tuning could match all these requirements. Bias stability over a 90 s horizon is a critical point to ensure an accurate calibration when required. A technological survey identified the quartz Vibrating Beam technology as still the best option to meet these requirements. Silicon Vibrating Beam is an emerging technology which retains some of the benefits of the former while reducing the cost and manufacturing complexity. Finally Silicon capacitive pendulum accelerometers are ubiquitous in the mass market and recent developments are pushing there capabilities toward the high-end market. A possible Inertial Measurement Unit based on the European SiREUS MEMS rate sensor has been designed in a preliminary way and its expected performance for and EDL mission has been validated through high-fidelity simulation. This work opens the way to future developments of a MEMS-based light-weight European Inertial Measurement Unit, integrating either existing accelerometers matching the derived requirements, or a new sensor developed specifically for space applications.

END OF DOCUMENT

rd9_accelerometer needs for imu - final report 23mar09

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