Navegação óptica espacial

1. Navegação óptica espacial José Manuel N. V. Rebordão Faculdade de Ciências da Universidade de Lisboa Ciência 2009, 30 de Julho de 2009

2. 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.

3. Optics / Photonics in Space • Instrumentation / Payload (‘all’ n) • 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

4. 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

5. 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, …

6. 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, …)

7. 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

8. Types • Passive • Camera-based / imaging • Terrain • Celestial bodies • Other spacecrafts (patterns of lights, 3D, …) • Active • LIDAR • Interferometric • Lateral sensing

9. 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

10. 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 Examples

11. Navigation & Positioning

12. ESA - AutoNav 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.

13. 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!

14. Autonav – Bright object detection • Small objects & phase correction • Full object within FOV • Limb measurement

15. FP7 - AEROFAST Solar 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.

16. Beagle 2 as seen from Mars Express ESA - Planav Precise determination of Beagle 2 landing position in Mars 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.

17. ESA - NPAL 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)

18. Courtesy 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.

19. 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

20. 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

21. Objective:Landing on a planet without atmosphere (Mercury) on a only 10% hazard-free surface Courtesy of EADS Astrium SAS Hazard avoidance (HA)is responsible for hazard detection and path-planning to avoid the detected hazards with constraints on fuel and spacecraft control authority. Vision Based Landing: objectives

22. 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).

23. ESA – VBrNav / HM Development of landing hazard maps (in view of Mercury or Mars landing), based on optical images using shape from shading methods.

24. 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

25. ESA - LiGNC LIDAR data processing to:- generate topographic maps of the landing regions, - build up landing hazard maps- estimate dynamically navigation kinematical parameters.

26. ESA - LiGNC

27. ESA – LAPS New Lidar developed for planetary topography Image processing (IP) consolidation Updating LiGNC IP algorithms for LAPS needs: Adaptation to LIDAR outputs Real-time implementation and optimization (with Vision-Box) Tests

28. Rendezvous & Docking VBrNav / RVD GNCO & GNCO Maturation PROBA 3

29. ESA – VBrNav / RDV 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 mm) • No zoom, only 1 fixed camera • Minimum number of light spots on the target • Eclipse

30. ESA – GNCO MATURATION Mars Return Sampler mission Modelling optical navigation sensors and image processing chain Development of performance models Laboratory test bed Real-time test bed with WH in the loop Passive spherical, non-stabilized white canister with RR

31. PROBA-3 ESA – PROBA 3

32. PROBA-3 Constellation / Instrument configuration

33. ESA - HPOM 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.

34. Laser & Detection FSI Head Optical Head FSI - Frequency Sweeping Interferometry • 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 • mm level accuracy at short ranges • Measurement of drift between S/C

35. 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

36. FSI for distance measurementCandidateTechnology for ESA PROBA 3 (2013)Vacuum tests in 2009

37. ESA - FEMTO Realisation 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

38. 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 Trilaterationscheme to obtain the lateral displacements and angular orientation of the DSC wrt the MSC with an absolute distance metrology system.

39. ESA- Mode Locked Semiconductor Lasers Modelocked Semiconductor Laser accurate timing stabilization Pulse Cross-correlation for time-of-flight distance measurement Application to space and to Formation Flying missions metrology

40. Mechanisms ! APS cameras ! 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

41. 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 !