Autonomous Vision Based Detection of Non-stellar Objects Flying in Formation with Camera Point of View

Similar documents
Autonomous Vision Based Detection of Non-stellar Objects Flying in formation with Camera Point of View

Measurements & Instrumentation Systems National Space Institute Technical University of Denmark

FIBER OPTIC GYRO-BASED ATTITUDE DETERMINATION FOR HIGH- PERFORMANCE TARGET TRACKING

THE MICRO ADVANCED STELLAR COMPASS FOR ESA S PROBA 2 MISSION

PRELIMINAJ3.:( 6/8/92 SOFTWARE REQUIREMENTS SPECIFICATION FOR THE DSPSE GUIDANCE, NAVIGATION, AND CONTROL CSCI. Prepared by

Onboard Maneuver Planning for the Autonomous Vision Approach Navigation and Target Identification (AVANTI) experiment within the DLR FireBird mission

Formation Flying and Rendezvous and Docking Simulator for Exploration Missions (FAMOS-V2)

New Worlds Observer Final Report Appendix J. Appendix J: Trajectory Design and Orbit Determination Lead Author: Karen Richon

BOWSER Balloon Observatory for Wavelength and Spectral Emission Readings

ONBOARD AUTONOMOUS CORRECTIONS FOR ACCURATE IRF POINTING

BERING A DEEP SPACE MISSION TO STUDY THE ORIGIN AND EVOLUTION OF THE ASTEROID MAIN BELT

Formation Flying System Design for a Planet-Finding Telescope-Occulter System

Feasibility of Using Commercial Star Trackers for On-Orbit Resident Space Object Detection

HERA MISSION & CM16 lessons learned

NEW HORIZONS PLUTO APPROACH NAVIGATION

ADCSS 2017: Sodern presentation

Goddard Space Flight Center

Vision-based navigation around small bodies

A Concept of Nanosatellite Small Fleet for Earth Observation

ExoplanetSat: A Nanosatellite Space Telescope for Detecting Transiting Exoplanets

Feedback Control of Spacecraft Rendezvous Maneuvers using Differential Drag

Hayabusa Status and Proximity Operation. As of September 2nd, 2005

Rosetta Optical Navigation

ESSE Payload Design. 1.2 Introduction to Space Missions

Visual Feedback Attitude Control of a Bias Momentum Micro Satellite using Two Wheels

Satellite Orbital Maneuvers and Transfers. Dr Ugur GUVEN

ASSESSMENT OF GNC IMPACTS OF CHEMICAL PLUME IMPINGEMENT IN THE CASE OF PRISMA IRIDES EXPERIMENT

AIM RS: Radio Science Investigation with AIM

Semi-Analytical Guidance Algorithm for Fast Retargeting Maneuvers Computation during Planetary Descent and Landing

UAV Navigation: Airborne Inertial SLAM

THE TRAJECTORY CONTROL STRATEGIES FOR AKATSUKI RE-INSERTION INTO THE VENUS ORBIT

The Quantum Sensor Challenge Designing a System for a Space Mission. Astrid Heske European Space Agency The Netherlands

Juno Status and Earth Flyby Plans. C. J. Hansen

Recent Advances and Low cost concept for the Gamma-Ray Lens Project MAX

David A. Surovik Daniel J. Scheeres The University of Colorado at Boulder

NEED OF SPACECRAFT FORMATION FLYING AND ITS COMPLEXITIES: AN OVERVIEW

Mission Design and Trajectory Analysis for Inspection of a Host Spacecraft by a Microsatellite by Susan C. Kim

Prospector-1: A Low-Cost Commercial Asteroid Mission Grant Bonin SmallSat 2016

Lunar Satellite Attitude Determination System

Improving Space Surveillance with Space-Based Visible Sensor

GUIDANCE, NAVIGATION, AND CONTROL TECHNIQUES AND TECHNOLOGIES FOR ACTIVE DEBRIS REMOVAL

Flight S4-002 Status of Hayabusa2: Asteroid Sample Return Mission to C-type Asteroid Ryugu. Yuichi Tsuda, Makoto Yoshikawa (ISAS/JAXA)

BIRDY-T : Focus on propulsive aspects of an icubsat to small bodies of the solar system

THE PRISMA FORMATION FLYING DEMONSTRATOR: OVERVIEW AND CONCLUSIONS FROM THE NOMINAL MISSION

Multi-aperture miniaturized star sensors, modular building blocks for small satellite AOCS systems

STAR SENSOR SPECIFICATION STANDARD

ADVANCED NAVIGATION STRATEGIES FOR AN ASTEROID SAMPLE RETURN MISSION

Analysis of Relative Motion of Collocated Geostationary Satellites with Geometric Constraints

Abstract HISAKI (SPRINT A) satellite is an earth orbiting EUV spectroscopic mission and launched on 14 Sep Extreme ultraviolet spectroscope (EX

Overview of China Chang'e-3 Mission and Development of Follow-on Mission

Flight S4-002 Status of Hayabusa2: Asteroid Sample Return Mission to C-type Asteroid Ryugu. Yuichi Tsuda, Makoto Yoshikawa (ISAS/JAXA)

JUpiter Icy Moons Explorer (JUICE) Status report for OPAG. N. Altobelli (on behalf of O. Witasse) JUICE artist impression (Credits ESA, AOES)

AUTONOMOUS AND ROBUST RENDEZVOUS GUIDANCE ON ELLIPTICAL ORBIT SUBJECT TO J 2 PERTURBATION.

OTSUKIMI Moon-sighting Satellite Kyushu Institute of Technology. 3 rd Mission Idea Contest UNISEC Global

PAVING THE WAY FOR FUTURE ON-ORBIT SERVICING MISSIONS: THE AVANTI EXPERIMENT

Current Status of Hayabusa2. Makoto Yoshikawa, Yuichi Tsuda, Hayabusa2 Project Japan Aerospace Exploration Agency

LOW-COST LUNAR COMMUNICATION AND NAVIGATION

Steeve Kowaltschek (ESA/ESTEC TEC-SAA) 17/10/ ADCSS. ESA UNCLASSIFIED - For Official Use

HYPER Industrial Feasibility Study Final Presentation Precision Star Tracker Activity 3, WP 3100

Learning Lab Seeing the World through Satellites Eyes

Proba-3 mission and the ASPIICS coronagraph

SELENE TRANSLUNAR TRAJECTORY AND LUNAR ORBIT INJECTION

THE JOINT MILLI-ARCSECOND PATHFINDER SURVEY (JMAPS): MISSION OVERVIEW AND ATTITUDE SENSING APPLICATIONS

Optical Tracking and Attitude Determination of LEO CubeSats with LEDs: A Balloon Demonstration

What is scan? Answer key. Space Communications and Navigation Program. Entering the Decade of Light.

Attitude Determination System of Small Satellite

Astrodynamics of Moving Asteroids

Technology Reference Studies

Automatic Star-tracker Optimization Framework. Andrew Tennenbaum The State University of New York at Buffalo

Feasible Mission Designs for Solar Probe Plus to Launch in 2015, 2016, 2017, or November 19, 2008

SAFETY GUIDED DESIGN OF CREW RETURN VEHICLE IN CONCEPT DESIGN PHASE USING STAMP/STPA

Rendezvous Maneuvers with Final Approach by R-bar to Target Satellite in Leo Orbit

DEVIL CHAPTER 6 TEST REVIEW

Exploring the Mysteries of the Cosmos on the MOST Microsatellite Mission

Relative Orbital Elements: Theory and Applications

Space Surveillance using Star Trackers. Part I: Simulations

Zero Reaction Maneuver: Flight Validation with ETS-VII Space Robot and Extension to Kinematically Redundant Arm

Sliding Mode Control Strategies for Spacecraft Rendezvous Maneuvers

ADVANCES AND LIMITATIONS IN A PARAMETRIC GEOMETRIC CORRECTION OF CHRIS/PROBA DATA

Attitude Determination and Control

Operational Aspects of Space Weather-Related Missions

Final Presentation of Assessment Star Tracker for Asteroid Search. By Peter Davidsen

9.2 Worksheet #3 - Circular and Satellite Motion

Spacecraft Angular Rate Estimation Algorithms For Star Tracker-Based Attitude Determination

Previous Lecture. Orbital maneuvers: general framework. Single-impulse maneuver: compatibility conditions

StellarXplorers IV Qualifying Round 2 (QR2) Quiz Answer Key

A Stellar Gyroscope for CubeSat Attitude Determination

Space Surveillance with Star Trackers. Part II: Orbit Estimation

Linked, Autonomous, Interplanetary Satellite Orbit Navigation (LiAISON) Why Do We Need Autonomy?

Attitude Determination using Infrared Earth Horizon Sensors

Hyperspectral at Leonardo. Ing. Alberto Sarti, CTO Electronic, Defense and Security Sector

Modeling, Dynamics and Control of Spacecraft Relative Motion in a Perturbed Keplerian Orbit

Precision Attitude and Translation Control Design and Optimization

AN ANALYTICAL SOLUTION TO QUICK-RESPONSE COLLISION AVOIDANCE MANEUVERS IN LOW EARTH ORBIT

Navigation and Control Design for the CanX-4/-5 Satellite Formation Flying Mission. Niels Henrik Roth

Research Article Generalized Guidance Scheme for Low-Thrust Orbit Transfer

LOTNAV. A Low-Thrust Interplanetary Navigation Tool: The Trajectory Reconstruction Module

SMALL SATELLITE ATTITUDE CONTROL FOR TRACKING RESIDENT SPACE OBJECTS

BINARY ASTEROID ORBIT MODIFICATION

Overview of Astronautics and Space Missions

Transcription:

Autonomous Vision Based Detection of Non-stellar Objects Flying in Formation with Camera Point of View As.Prof. M. Benn (1), Prof. J. L. Jørgensen () (1) () DTU Space, Elektrovej 37, 4553438, mb@space.dtu.dk, jlj@space.dtu.dk Keywords: ASC, Advanced Stellar Compass, VBS, Vision Based Sensor, PRISMA ABSTRACT The µ-advanced Stellar Compass (µasc) is a camera system which autonomously can provide attitude information based on the stars. An extended functionality of the µasc, called the Vision Based Sensor (VBS), enables the camera system to render rendezvous and docking navigation information for a formation flying spacecraft. The VBS system facilitates different operation modes, enabling 6DoF solutions for spacecraft flying in close proximity, and inertial Line-of-Sight (LoS) solutions for any spacecraft reflecting more light than an Mv7 star. This paper will focus on the LoS solutions of the VBS system, with a thorough analysis of inflight performance and future mission aspects. The VBS system is currently running on the PRISMA mission launched in 1, where it functions as a part of the instrument package forming the rendezvous and docking navigation test bench for the Main spacecraft. Here the VBS system has been enabled based on the scheduled flight maneuvers in between the two spacecraft, autonomously providing the Main spacecraft with pose and position or LoS information of the Target spacecraft. During different phases of the mission, full centroid information was captured from the Camera Head Units (CHUs) of the µasc, which for these periods have enabled on-ground VBS reprocessing and deeper investigation of the detected objects and their statistical occurrences. The PRISMA mission facilitates a total of four CHUs where two are dedicated for normal startracker operation and the other two CHUs are dedicated for VBS operation, one for short range constellation and one for far range inertial LoS operation. The captured data used for the analysis presented in this paper, includes centroids from the VBS CHU dedicated for inertial LoS operation and from the two standard startracker CHUs. By combining the data from these three CHUs, a total of 3 hours of operation distributed over the entire year is included in the thorough data analysis and performance characterization. The analysis has provided a great overview of performance for the LoS detection capabilities of the VBS system. This includes inertial pointing accuracy vs range for a known target spacecraft, robustness of the autonomous behavior and frequency of detected non-stellar objects flying in low-earth orbit. This paper will present the methods of analysis used for treading the vast amount of inflight data together with the outcome of the VBS algorithms and the performance of the system. In conclusion the paper provides expected performance overview for use

of the VBS instrument for future low-earth orbit missions as well as for deep space missions, including sample return. 1. Vision Based Sensor The Vision Based Sensor (VBS) is an instrument capable of autonomously determining relative pose and position between two spacecrafts flying in close formation, or provide line-of-sight solutions for distant flying objects/spacecrafts. Solution information is based on digital images captured using cameras placed on a spacecraft tracking Non-stellar Objects (NSOs) of interest in the Field-of-View (FOV) of the imaging camera. The VBS system is realized as an extension module to an already space proven instrument, the µ-advanced Stellar Compass (µasc), which is capable of fully autonomous delivery of high precision attitude references based upon star observations []. The VBS system utilizes the µasc imaging platform either with specific VBS Camera Head Units (CHUs) for Short Range (SR) operations or using the standard star tracker CHUs for Far Range (FR) operations. Figure 1: System elements of the µ-advanced Stellar Compass, depicting a CHU, a baffle and a redundant double µdpu. By providing either pose and position of a spacecraft or line-of-sight information of NSOs to the onboard Guidance, Navigation and Control (GNC) unit, the VBS system enables closed loop formation flying, rendezvous and docking capabilities. The PRISMA satellite mission is the first to utilize the VBS system on the implemented µasc of the Main spacecraft, using the VBS solutions in the GNC core to perform closed loop formation flying with the Target spacecraft. The PRISMA project, which is led by the Swedish Space Cooperation [1], is a technical demonstration mission, constituting of an in-orbit test bed for GNC algorithms as well as sensors for rendezvous and closed-loop formation flying based on a Main and a Target spacecraft. The VBS system is one of three systems on the PRISMA mission for relative position determination of the Target spacecraft.

The configuration of the µasc for PRISMA consists of a total of four CHUs: One standard low light CHU capable of detecting stars and is used by the VBS system for far range operations. One high light CHU with a fixed aperture and filter included and is used by the VBS system for close range operations. And two standard star tracker CHUs reserved for attitude determination. The placement of the VBS CHUs on the PRISMA spacecraft is illustrated in Figure, where the two standard CHUs are placed on the backside of the Main spacecraft. Figure : Main and Target layout in flight configuration of the PRISMA mission (Image: [1]) Further information regarding the VBS system on PRISMA is presented in [3,4,5,6].. Rerun of VBS Algorithms on Recorded Centroids The VBS system as implemented on PRISMA is designed to output only the best detected Target spacecraft candidate for line-of-sight solutions. The VBS does however internally keep track of several object trajectories simultaneously, which are of interest for analyzing the availability of tracked objects, frequency of detections and have precise information of the best candidate for a Target object. An on-ground VBS rerun of the inflight recorded centroids from the PRISMA mission has provided such information, which are the data presented in this paper. Three of the CHUs on PRISMA are capable of determine attitudes and provide centroid information of the detected objects on the image sensor, namely, CHU A, B

and C. The centroid information is available from the µasc on request, and on the PRISMA mission a total of ~3hours of centroids have been recorded at Hz. By combining these centroids with the determined attitude information, the centroids can be split up into detected stars and into detected Non-stellar Objects. Stars are already known to the VBS system whereas the Non-stellar Objects are the objects of interest for tracking. In Figure 3 is illustrated the time periods for which the µasc has detected NSOs during the PRISMA mission. The splitting into the different CHUs are illustrated due to the fact that the CHUs have had different purposes during the PRISMA mission. Likewise, in Table 1 is given the total number of NSOs for reprocessing by the VBS algorithms..5 x 16 Number of Recorded NSO Objects for the µasc on PRISMA CHU A CHU B CHU C Recorded NSO Objects 1.5 1.5 CHU A 898486 CHU B 15754 CHU C 17739 Total 616549 Table 1: Total number of Non-stellar Objects detected. Q-1 Q3-1 Q4-1 Q1-11 Q-11 Q3-11 Q4-11 Q1-1 Time UTC Figure 3: Recorded Non-stellar Objects from PRISMA mission. 3. Tracked Objects The VBS algorithms used for rerunning the NSOs are similar to the inflight algorithms on the µasc with the addition of included probes for extracting the state of tracked objects. In order to determine a correlation between the detected NSOs, the VBS are accepting objects that are moving within a certain bandgap of inertial angular velocities. As soon as an NSO has 3 sequential detections, the NSO is marked as an object for tracking. This gives that the greater the tracking history, the greater the confidence of the tracked object is. The inertial velocity bandgap is based on the fact that the PRISMA satellites are orbiting the Earth in a Low-Earth Orbit (LEO), with an orbital period of T 1min. By assuming that the Main spacecraft are following the Target spacecraft in a circular orbit, the inertial angular velocity of Target as observed by Main can be expressed by: o δθ 36 ω = = = 16 " s δt 1 min In order to detect as many objects as possible for the rerun, the bandgap limits are set in the range of 1 /s to 5 /s for input to the VBS algorithms.

Detected Centroids of Tracked Objects for CHU A with Tracking History > 1 1 CHU A Detected Centroids of Tracked Objects for CHU A with Tracking History > 3 3 4 4 5 5 1 3 4 5 6 7 1 a) 1577 tracked objects 1 1 CHU B 3 4 5 5 3 4 5 6 7 1 c) 35 tracked objects 1 1 CHU C 3 4 5 5 3 4 5 6 3 4 5 6 7 3 4 Detected Centroids of Tracked Objects for CHU C with Tracking History > 1 7 d) 38 tracked objects Detected Centroids of Tracked Objects for CHU C with Tracking History > 6 3 4 5 Detected Centroids of Tracked Objects for CHU B with Tracking History > 1 3 4 b) 53 tracked objects Detected Centroids of Tracked Objects for CHU B with Tracking History > 7 e) 919 tracked objects 1 3 4 5 6 7 f) 18 tracked objects Figure 4: Detected centroids of objects tracked by the VBS system. The data is divided on CHUs. Left column for tracking history > and right column for tracking history >. The colors separate the different trackings. In Figure 4 are illustrated all the detected tracks on the CCD plane as seen by the three CHUs. The difference in the tracks inbetween the CHUs are clearly given, which are due to the different usage of the CHUs: CHU A has been recording centroids during an inertial pointing stability test pointing perpendicular to the orbit plane. This has resulted in tracking of relative circular motions of objects in almost parallel orbits as PRISMA. CHU B has been recording centroids during normal operation while pointing ~45º off the orbit plane.

CHU C has been recording centroids mainly with the Target spacecraft in FoV while pointing along the orbit flight path. In Figure 5 are illustrated the tracking characteristics with respect to tracking history and angular velocities for the three CHUs. The long durations of steady inertial pointings with CHU A have resulted in accomplishing great tracking history of detected objects. Additionally, fast moving objects following along-track the spacecraft are detected. CHU B reflect tracking of objects that are similar to each other, while CHU C is very likely to have the Target spacecraft available for tracking, illustrated by the peak in angular velocities. a) b) Representation of the Sequential Tracked Objects 1 5 1 4 CHU A CHU B CHU C 1 4 1 3 Number of Tracked Objects based on Angular Velocities CHU A CHU B CHU C Sequential tracking history 1 3 1 1 1 Number of tracked objects 1 1 1 1 1 1 1 1 1 3 1 4 Number of tracked outputs 1 1 3 4 5 6 7 Bins of mean angular velocity ["/s] Figure 5: Tracking characteristics for the three PRISMA CHUs. (a)tracking history, (b) Angular velocity. 4. Frequency of Tracked Objects While orbiting the Earth at a rather constant rate, it is desired to analyze at which frequency newly detected objects occur. This will provide with information about how many objects will get into detection range and how often they occur. In Figure 6 are illustrated the time difference between newly tracked objects with three different limitations, namely, for tracking histories of 1, 1 and 1. For objects with a tracking history of 1 is not yet in a stable history range for providing great confidence on the track. It is seen that these occurs at frequency peaks around.5s, 1s, s and 4s, which are closely related to the updating frequency of Hz for the µasc imaging system. For the case with a minimum of 1 in history tracking, the peak shifts since the newly detected trackings with this history occurs less frequently. Furthermore, a peak at the frequency of the orbital period of PRISMA occurs, which is due to repeated detections of objects flying in similar or crossing orbits. The last illustration including objects with a tracking history greater than 1, shows that the peak shifts even closer to the orbital period of PRISMA. The main peak is still below the orbital period mark, which gives that newly tracked objects with high confidence are occurring several times over just one orbit period.

a) b) Time Difference Between Detection of NSOs with a Tracking History of 1 Time Difference Between Detection of NSOs with a Tracking History of 1 5 5 Detections PRISMA Orbit Period Detections PRISMA Orbit Period 4 Number of detected objects in bin Number of detected objects in bin 45 35 3 5 15 1 15 1 5 5-1 1 1 1 3 4-1 1 5 1 1 1 1 Bins of time difference between detections [s] 1 1 1 3 4 1 1 1 1 Bins of time difference between detections [s] 5 1 c) Time Difference Between Detection of NSOs with a Tracking History of 1 16 Detections PRISMA Orbit Period Number of detected objects in bin 14 1 1 8 6 4-1 1 1 1 3 4 1 1 1 1 Bins of time difference between detections [s] 5 1 Figure 6: Detection frequency of new tracked objects. The graphs illustrates histograms for objects with tracking history of (a) 1 and above, (b) 1 and above, (c) 1 and above. 5. Pointing Accuracy towards Known Target In order to analyze performance of pointing accuracy, data including tracking information of the Target spacecraft is extracted from CHU C in order to have a known Target candidate. The data extracted are illustrated in Figure 7 for all the different trackings. a) b) Tracked CCD Centroids of Target Spacecraft Tracked Inertial Pointing to Target Spacecraft 8 1 6 4 Dec [ ] 3-4 -4-6 5-8 1 3 4 5 6 7 5 1 15 RA [ ] 5 3 35 Figure 7: Tracking of known Target spacecraft. (a) The tracks at detected by the CCD. (b) The inertial pointing of the tracking. The colors separate the different trackings.

The VBS algorithms are performing running average of the tracked objects in order to predict the next possible inertial pointing towards the object. In Figure 8 is illustrated the comparison between the VBS predicted inertial pointing and the actual detected inertial pointing towards the tracked object, together with the expected maximum deviation over distance. The theoretical expected maximum is based on the angular size of the Target spacecraft from where reflections can occur, together with the centroiding accuracy of the µasc system. It is seen that for distances below 1km the deviation is within the expected maximum, but the few samples at ~3km is just on the boundary. This can be due to acceleration of the Target spacecraft during approach and recede maneuvers. 1 1 Deviation Between Predicted VBS Pointings and Detected Pointings Over Distance from Main to Target VBS Output Theoretical Max Mean prediction deviation ["] 8 6 4.5 1 1.5.5 3 3.5 Distance between Main and Target [m] x 1 4 Figure 8: Detection precision vs. the distance between Main and Target. 6. Future Implementations The VBS algorithms are currently flying on the JUNO mission on-route to Jupiter, which will start orbiting Jupiter in 16. The main objectives for the VBS system are to detect asteroids on its route to Jupiter, as well as detection of minor moons when arriving at Jupiter. Next generation of the VBS system is planned for Proba-3 flying in a Highly Elliptical Orbit (HEO) with a configuration for LoS solutions and 6DoF solutions for the VBS system, providing an Occulter spacecraft with GNC information for flying in controlled formation with a Coronagraph spacecraft. This mission has to operate at a distance of 15m, which is three times the maximum distance experienced for 6DoF solutions on the PRISMA mission. This requires a redesign and optimization of the imaging CHU for the given scenario. Other Rendezvous and Docking missions are already on the drawing board for including VBS functionalities, using CHUs which includes a µ-inertial Reference Unit (MIRU) that provides high frequency attitude solutions. This will accelerate both inertial attitude determination and expand the 6DoF solution range for the VBS system.

7. Conclusion By post-processing of inflight recorded centroid data, it has been shown that the VBS system is very much capable of detecting and tracking several Non-stellar Objects simultaneously. From a satellite orbiting the Earth, all satellites detectable by the star tracker CHUs can be tracked as soon as their inertial angular movement, with respect to the Main satellite, fits within the bandpass values provided to the VBS system. The VBS system is capable of providing high accuracy inertial pointings of all tracked objects in combination with key tracking information, that can be used for determine the confidence and precision of the detected object. Furthermore, dependent on which NSO object that are of interest to search for, different boresight pointings relative to flight path have shown a wide covering range for tracking of fast and slow moving NSOs. By providing inertial pointing towards any Non-stellar Object to a GNC core, approach maneuvers can easily be performed in the right direction. The VBS system is fully autonomous and can detect objects as soon as they can be detected by the star tracker CHUs. This is especially useful for missions with limited commandability, such as e.g. Sample-Return missions. 8. References 1. Persson, S., Bodin, P., Gill, E., Harr, J. and Jørgensen, J.L. PRISMA An Autonomous Formation Flying Mission, European Space Agency, 65 SP, 6.. Denver, T., Jørgensen, J.L., Michelsen, R. and Jørgensen, P.S. MicroASC Star Tracker Generic Developments, Small Satellite Systems and Services Symposium, Chia Laguna, Sardinia, Italy, 5-9 Sept. 6. 3. Benn, M. Design of a Visual Rendezvous and Docking Navigation Sensor, Master Thesis Project at the Danish Technical University, 7. 4. Benn, M. Short Range Pose and Position Determination of Spacecraft Using a µ- Advanced Stellar Compass. 3 rd International Symposium on Formation Flying, Missions and Technologies, ESTEC, Apr 8 5. Benn, M. Range Management of a Vision Based Rendezvous and Docking Navigation Sensor. International Astronautical Congress, Daejeon, Korea, Oct 9. 6. Bjarnø, J. B. Short range camera for Rendezvous in Space, Performance and scenario study of the VBS system, DTU Space, Dec 5.