Navegação óptica espacial
José Manuel N. V. RebordãoFaculdade de Ciências da Universidade de Lisboa
Ciência 2009, 30 de Julho de 2009
2009
Abstract Autonomous navigation of spacecrafts is a mandatory technology in
the context of a wide variety of space missions, such as rendezvous and docking, landing or constellation management. Sensing systems, in particular active or passive optical sensors, play an unique role to feed GNC systems with suitable spatial and temporal data. In addition noise characteristics are critical to select and parameterise signal processing filters and ensure smooth navigation.
Since Portugal became a member of ESA, optical navigation has been addressed by Portuguese research units and companies, working in most of the cases in close collaboration with EADS-Astrium, and several projects were awarded to develop and consolidate technologies and to generate performance models to guide the specifications and development of the GNC chain. Slowly but effectively, the TRL level has been increasing, leading to flight experiments and demonstrations in realistic environments under preparation to flight in ESA / Proba 3.
Several optical navigation techniques will be presented in the context of the control of constellation configurations, terrain-related navigation, rendezvous between autonomous spacecrafts and generation of hazard maps to enable the selection of the less hazardous landing site, supported by optical metrology and imaging or lidar data.
2009
Optics / Photonics in Space
Instrumentation / Payload (‘all’ ) Analogue & Digital optics Focal plane / sensors P/L design assessment, performances & telemetry
Spacecraft / System Attitude and navigation sensors GNC sensors Configuration management Harness Optical communications Structure monitoring (FO sensors) OGSE
2009
What type of Missions ? Autonomous missions
Solar system exploration Man cannot be on-the-loop
Constellation of spacecrafts (S/C) Real-time configuration control System of several specialized S/C Multi-aperture Instruments
Metrology
2009
Functions to be performed
Relative navigation wrt Terrain Stars (star mappers, star trackers, sun sensors) Planets & small bodies (Earth sensors)
Landing Hazard mapping (in the context of Hazard Avoidance)
Rendezvous & Docking Range and attitude estimation
Instrument enablers Configuration determination
Ranges, angles ( and corresponding velocities and accelerations)
Configuration keeping Manoeuvring control
Pointing, change of geometry / baseline, …
2009
Optics plays a role Supplying derived data to the GNC system Complementing / filtering / improving other
navigation sensors with redundant data IMU
Embedded in a chain of several variable accuracy and time response sensors (metrological chain) RF Others (optical, …)
2009
Main interfaces / dependencies
ADCS Attitude Determination & Control Systems
GNC Guidance, Navigation & Control
System level Type and degree of S/C stabilization Location in S/C Thrusters influence
2009
Types Passive
Camera-based / imaging Terrain Celestial bodies Other spacecrafts (patterns of lights, 3D, …)
Active LIDAR Interferometric Lateral sensing
2009
Constrains and critical tradeoffs
Mechanisms Zooming variable resolution Angular steering focus of attention
Power LIDAR
System Redundancy Radiation hardening
Processing power & Bandwidth (>>) 1 – 10 Hz Image-related Intelligent processing Number of devices
Mission-related Timing
Thermal illumination, shadows, … Eclipse / non-eclipse
2009
Examples Landing / Hazard
mapping Passive
VBrNav HASE
Active LiGNC LAPS
Rendezvous & Docking VBrNav GNCO PROBA 3
ESA Missions PROBA 3 Mars Return Sampler Next Moon Lander
Navigation & Positioning AUTONAV AEROFAST NPAL PLANAV
Constellation / Instrument configuration
High Precision Optical Metrology (DARWIN) Fabry-Perot Metrology PROBA 3
FEMTO (XEUS) Mode Locked Semiconductor Lasers
Navigation & Positioning
2009
ESA - AutoNavAutonomous on-board navigation for interplanetary missions
Partners ESA, EADS Astrium (Fr), GMV (Sp), BDL
Funding ESA
Contracts ESA EADS Astrium INETI
Start September 2001
End July 2004
Simulation of the navigation optical camera, to be included into the general system simulator; generation of images of star fields, planets and asteroids.
Image analysis of star fields, asteroids and planets in order to measure the attitude of spacecraft and contour / limb of asteroids, enabling autonomous relative navigation.
2009
Autonav – Faint object detection
To locate a non-resolved faint punctual object using multiple time integration (MTI) approach to increase the SNR, and 3x validation based on the linearity of displacement.
20 to 30 images are accumulated in sequence, … made overlap using guide stars and added to increase SNR The process is repeated three times to discriminate faint fixed
stars from faint moving bodies (asteroids or comets) Magnitude 13 objects should be detected with MTI The soonest asteroids are detected, the more
accurate navigation is! For n frames:
Find candidate pointswithin ROI
List of candidate LOS:- positions (ICRS and sub-pixel image coords)
- instrumental magnitudes
Attitude Measurement(ref. image)
Provide ref. imagewith ICRS
coordinatesand guide stars
(identifiedcatalogue stars)
Locate guide stars
Geometric superposition ofROIs
Accumulate data within theROI
ROI radiometricprocessing
REAL TIME
- Reference image;- Search window
(ROI)Single or multi-frame image
(1,...,n), for MTI
IP_I
nit_
LOS_
Mea
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IP_MTI_LOS_Measurement
IP_F
inal_L
OS_
Mea
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2009
Autonav – Bright object detection
Small objects & phase correction Full object within FOV
Limb measurement
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2009
FP7 - AEROFASTAEROcapture for Future spAce tranSporTation
Partners Astrium (Fr), Deimos Engenharia, Corticeira Amorim (PT), Samtech (B), U. Rome, STIL (Bu), I. Lotnictwa (Pl), SRCPAS (Pl), ONERA (Fr), Kybertec (CZ)
Funding FP7
Contracts EADS Astrium SAS INETI
Start September 2008
End 2010Solar system missions (e.g., Mars) relying on return missions (humans and cargo) must rely on
aerocapture to be mass effective and use atmospheric drag to slow space vehicles.
Aerocapture demands extremely accurate navigation
Image-based optical navigation (images of planet limbs, stars and asteroids) to support GNC.
2009
ESA - PlanavImage based navigation tool for Mars landing
Partners ESA, Deimos Engª (P)
Funding ESA (Task Force Portugal – ESA)
Contracts ESA Deimos Engª INETI
Start August 2003
End December 2003
Utilization of the geophysical cameras of Beagle in the opposite direction, to track Mars moons Phobos and Deimos, against a fixed background of bright stars.
Analysis of the visibility of stars and moons, to ensure that the Kalman filter receives an adequate number of observables, in order to reduce the positional error of Beagle 2.
Precise determination of Beagle 2 landing position in Mars
Beagle 2 as seen from Mars Express
2009
ESA - NPALNavigation for planetary approach and landing
Partners ESA, EADS Astrium (Fr), O. Galileo (It), U. Dundee, SSSL (Uk), Atmel (It)
Funding ESA
Contracts ESA EADS Astrium INETI
Start December 2001
End July 2004
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Image analysis of planetary surfaces (feature detection and tracking) in order to enable navigation relative to the terrain (kinematics).
Modelling and testing image processing algorithms hardcoded in one ASIC (FEIC camera)
2009Courtesy of EADS Astrium SAS
NPAL – Relative Navigation issues
Supported by vision Last 20 km in about 60
s. Relative surface velocity
from ~750 m/s to 0. FOV 70º 1024x1024. 50 Hz
Thermal constrains: Landing at dawn Sun very close to the
horizon (< 5º) long shadows.
2009
NPAL – Relative Navigation issues
With a single measurement, the LOS to a feature point is known, but not its depth.
Tracking the point with a dynamical filter allows progressive determination of depth. For that:
Displacement and rotation of the S/C between two consecutive measurements MUST be known.
Rotation gyroscopes
Displacement requires v, but errors in v grow, because v is integrated from a.
The vehicle state estimation is performed through sequential Kalman filtering (one sub-optimal implementation, Sparce Weight Kalman Filter, tested)
~ 50 points are used in the state vector
Terrain-relative navigation. What for?
For safe landing with vision-based risk assessment (hazard mapping) and Hazard Avoidance
Passive systems (camera)VBrNav HASE NextMoon
Active systems (lidar)LiGNC LAPS NextMoon
2009
Vision Based Landing: objectives
Courtesy of EADS Astrium SAS
Objective: Landing on a planet without atmosphere (Mercury) on a only 10% hazard-free surface
Hazard avoidance (HA) is responsible for hazard detection and path-planning to avoid the detected hazards with constraints on fuel and spacecraft control authority.
2009
Vision based Landing: Hazard Avoidance (HA) Hazard Mapping: process of
analysing terrain topography and detecting hazards through IP algorithms applied to the monocular optical images taken by the onboard navigation camera.
Piloting: concepts of data fusing, planning and decision-making used for the selection of a safe Landing Site (LS).
Guidance: concepts used to steer the spacecraft to the Landing Site (it can change during flight).
2009
ESA – VBrNav / HMVision-Based relative Navigation techniques framework
Partners ESA, LusoSpace, Deimos Engª (P), EADS Astrium (F)
Funding ESA (Task Force Portugal – ESA)
Contracts ESA Deimos Engª INETI
Start February 2004
End March 2006
Development of landing hazard maps (in view of Mercury or Mars landing), based on optical images using shape from shading methods.
2009
HM issues Topography (slope) estimation
using different IP methods Motion Stereo Optical flow Shape from Shading (SFS) Merging with Navigation DEM0
Image analysis to derive Shadows Texture (boulders and craters)
Hazard fusion
Pangu topo Reconstructed DEM
Camera Image Reconstructed Image Difference Image (log)
De-striped DEM
Pangu slope map Recovered slope map Slope differences (log)
2009
ESA - LiGNCLIDAR Guidance, Navigation and Control
Partners ESA, EADS Astrium (Fr), Deimos Engª, Solscientia (P), U. Dundee (Uk)
Funding ESA
Contracts ESA EADS Astrium INETI
Start September 2001
End July 2005
LIDAR data processing to:- generate topographic maps of the landing regions,
- build up landing hazard maps- estimate dynamically navigation kinematical parameters.
2009
ESA - LiGNC
2009
ESA – LAPSLIDAR-based Autonomous Planetary landing System
Partners EADS Astrium SAS (Fr), ABSL Space Products (Uk), Vision-Box (Pt), U. Dundee (Uk)
Funding ESA
Contracts ESA EADS Astrium FCUL
Start 2008
End 2010
New Lidar developed for planetary topography Image processing (IP) consolidation
Updating LiGNC IP algorithms for LAPS needs:
Adaptation to LIDAR outputsReal-time implementation and optimization (with Vision-Box)Tests
XLIF
YLIF
ZLIF
Rendezvous & Docking
VBrNav / RVDGNCO & GNCO Maturation
PROBA 3
2009
ESA – VBrNav / RDVVision-Based relative Navigation techniques framework
Partners ESA, LusoSpace, Deimos Engª (P)
Funding ESA (Task Force Portugal – ESA)
Contracts ESA Deimos Engª INETI
Start February 2004
End March 2006
GNC (Guidance, Navigation & Control) for Rendezvous & Docking between autonomous S/C (in view of Mars Return Sample mission)
Design Drivers Early detection of the target for a specified radial
dispersion (50, 100 m) at a specified range (1, 1.5, 2 km)
±1º attitude uncertainty of the chaser Space qualified CCD (1024x1024, 15 m) No zoom, only 1 fixed camera Minimum number of light spots on the target Eclipse
2009
ESA – GNCO MATURATIONGuidance for Non-Circular Orbits
Partners Deimos Engenharia
Funding ESA (Task Force Portugal – ESA)
Contracts
Deimos Engenharia FCUL
Start January 2006
End December 2010Mars Return Sampler mission
Modelling optical navigation sensors and image processing chain
Development of performance modelsLaboratory test bedReal-time test bed with WH in the loop
Passive spherical, non-stabilized white canister with RR
-0.08-0.06
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x 10-3 CAN RR Focal plane coordinates
2009
PROBA-3
ESA – PROBA 3Autonomous Rendezvous Experiment
Partners Deimos Engenharia, …
Funding ESA
Contracts Deimos Engenharia INETI
Start 2009
End 2012
Constellation / Instrument configuration
PROBA-3
2009
ESA - HPOMHigh precision optical metrology (Darwin)
Partners ESA, EADS Astrium (Fr + D), SIOS, TPD/TNO (Nl), EADS-CASA (Sp)
Funding ESA
Contracts ESA EADS Astrium INETI
Start December 2001
End December 2005
DARWIN is based on an InfraRed Space Interferometer (MAT) to detect planets in non-solar planetary systems. Optical metrology (FSI, frequency sweeping interrferometry) for formation flying missions
New concepts for compensation of metrological networks in space.
2009
FSI - Frequency Sweeping Interferometry
Laser & Detection
Optical Head
FSI Head
ESA / FP-MET – Fabry-Perot Metrology
Non ambiguous measurement
No need for frequency stabilization
Low hardware complexity (transferred to software)
Compactness
Synthetic wavelength down to the mm range
m level accuracy at short ranges
Measurement of drift between S/C
2009
FSI for Multiple Aperture telescopes
.
Synthetic optics, Michelson configuration
Stabilization of the interference patterns
Metrological chain to control the optical delay lines
FSI for coarse compensation, relative metrology for RT stabilization
2009
FSI for distance measurement
CandidateTechnology for ESA PROBA 3 (2013)
Vacuum tests in 2009
2009
ESA - FEMTOAbsolute long distance measurement with
(sub-)μm accuracy for formation flight applications
Partners ESA, TPD/TNO (Nl), LCVU (Nl), ASTRIUM (D)
Funding ESA
Contracts ESA TPD/TNO INETI
Start January 2007
End December 2009Realisation and fundamental technological
limitations of pico (ps, 10-12s) and femto-second (fs, 10-15s) metrology
Assessment of the maturity of the technology
Applicability of fs-metrology to different space mission scenarios
Complexity and impact at system level
2009
Baseline Metrology for XEUS
XEUS (X-ray Evolving Universe Spectroscopy): two separate spacecrafts flying in formation with a focal length of 35 m, without the use of a large deployable bench or a telescope tube system.
XEUS Optical metrology must measure all 6 degrees of freedom of DSC (Detector S/C) relative to MSC (Mirror S/C),
The solution to measure 6 DOF is to use a Trilateration scheme to obtain the lateral displacements and angular orientation of the DSC wrt the MSC with an absolute distance metrology system.
>>10 arcsec – 10 arcsec0 degreesroll
10 arcsec – 1 arcsec0 degreespitch & yaw
170 µm – 125 µm0 m ± 1 mx & y
300 µm – 10 µm35 m ± 1 mz (ISD)
Uncertainty (2σ) Required – Predicted
Value and Range
Parameter
>>10 arcsec – 10 arcsec0 degreesroll
10 arcsec – 1 arcsec0 degreespitch & yaw
170 µm – 125 µm0 m ± 1 mx & y
300 µm – 10 µm35 m ± 1 mz (ISD)
Uncertainty (2σ) Required – Predicted
Value and Range
Parameter
2009
Mode locked Semiconductor Lasers for Optical Precision Metrology
Partners EADS Astrium (D), Reflekron (Fi)(observers)
Funding ESA – ITI (Industrial Triangular Initiative)
Contracts ESA FCUL
Start 2008
End 2010
Modelocked Semiconductor Laser accurate timing stabilization
Pulse Cross-correlation for time-of-flight distance measurement
Application to space and to Formation Flying missions metrology
ESA- Mode Locked Semiconductor Lasers
2009
Final comments (excluding Configuration-type issues)
Solid-state lasers Multi-camera
Redundancy
Zooming Changing FOV / resolution
Steerability Eclipse / non-eclipse phases Huge amount of on-board
Processing capability Telemetry Intelligence
Mechanisms !
APS cameras !
2009
Acknowledgements INETI FCUL
Bento Correia (now @ Vision Box) Alexandre Cabral Paulo Motrena Manuel Abreu João Coelho Conceição Proença João Dinis Elena Duarte
ESA EADS Astrium GNC team Deimos Engenharia GNC team
END !