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.

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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

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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

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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, …

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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, …)

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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

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Types Passive

Camera-based / imaging Terrain Celestial bodies Other spacecrafts (patterns of lights, 3D, …)

Active LIDAR Interferometric Lateral sensing

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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

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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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Autonav – Bright object detection

Small objects & phase correction Full object within FOV

Limb measurement

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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.

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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

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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.

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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

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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

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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 !