Radio-Frequency Sensor Fusion for Relative Navigation of ...

Technische Universität München

Radio-Frequency Sensor Fusion for Relative Navigation of Formation Flying Satellites G. Allende-Alba (TUM/IAPG) S. D‘Amico (DLR/GSOC) O. Montenbruck (DLR/GSOC)

5th International Conference on Spacecraft Formation Flying Missions and Technologies. May 29-31 (2013) > G. Allende-Alba


Contents ¾ Formation flying (FF) and relative navigation in space ¾ Motivation ¾ Techniques

¾ The PRISMA mission ¾ Sensor fusion ¾ ¾ ¾ ¾

Introduction Proposed architecture Measurements Relative navigation filter

¾ Results and disussion ¾ Conclusions and future work

Artist’s impression of future applications of formation flying satellites based on the PRISMA mission results (Source: SSC)


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FF and relative navigation in space: motivation ¾ Spacecraft formation flying applications ¾ SAR interferometer and gravimeter ¾ Multi spacecraft telescope ¾ On-orbit servicing and rendezvous

¾ Formation control -> relative navigation ¾ Autonomous systems require information with high levels of ¾ Robustness ¾ Reliability ¾ Availability

Artist’s impression of the DARWIN constellation. (Source: ESA). Artist’s impression of a typical on-orbit servicing mission. (Source: ATK) 5th International Conference on Spacecraft Formation Flying Missions and Technologies. May 29-31 (2013) > G. Allende-Alba

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FF and relative navigation in space: techniques ¾ Differential GPS ¾ Based on spaceborne GPS sensor ¾ Various degrees of accuracy

¾ Radio-frequency (RF) ¾ Formation flying radio-frequency (FFRF) sensor ¾ Self contained relative navigation system ¾ Coarse positioning and formation acquisition

¾ Vision-based ¾ Proximity and rendezvous operations

¾ Laser metrology

Artist’s impression of the VBS in PRISMA (Source: SSC)


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The PRISMA mission ¾ Demonstration of techniques for FF and rendezvous ¾ Novel relative navigation sensors

¾ Launched on June 15th, 2010 ¾ Sun-synchronous orbit ¾ Altitude of 750 km

¾ Joint effort ¾ ¾ ¾ ¾ ¾

Swedish National Space Board (SNSB) Swedish Space Corporation (SSC) / OHB-Sweden German Aerospace Center (DLR) National Center for Space Studies (CNES) Technical University of Denmark (DTU)

¾ Space segment consists of 2 spacecraft

Artist’s impression of the PRISMA satellites in orbit. (Source: DLR)

¾ Mango (chaser) ¾ Tango (target)


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Sensor fusion: introduction

¾ Absolute position of Mango and Tango ¾ Earth-Fixed EarthCentered reference frame

¾ Relative distance (d) ¾ Line of sight (LOS) ¾ RF reference frame


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Sensor fusion: architecture


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Sensor fusion: measurements Assessment of FFRF LOS measurements (DLR‘s POD as reference) Oct 28th (16:00) – Oct 30th (18:30), 2010 Large angular excursion (measurement error) caused by multipath during maneuver execution


Non-constant bias attributed to variations in sensor temperature

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Sensor fusion: measurements Assessment of (D)GPS measurements (DLR‘s POD as reference) Oct 28th (16:00) – Oct 30th (18:30), 2010


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Sensor fusion: relative navigation filter


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Results and discussion ¾ Accuracy of relative navigation solution ¾ Premise for analysis of filter properties ¾ Should be similar regardless of the sensor(s) being used

¾ Using both sensors at same orbit phases ¾ Increased robustness ¾ Increased reliability

¾ Handover between sensors at different orbit phases ¾ Increased availability

¾ In-plane relative navigation solution (Oct 28th (16:30) – Oct 30th (18:30), 2010)


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Results and discussion Initial assessment of accuracy Oct 28th (16:00) – Oct 29th (01:00), 2010

Formation in free drift and stand-by (approx. avg. ISD of 300 m) Sensor

Error in position (cm)

Error in velocity (mm/s)

Radial

Along-track

Cross-track

Radial

Along-track

Cross-track

FFRF

0.1±2.7

-0.3±2.3

1.4±12.6

-0.010±0.10

0.001±0.04

0.063±0.15

GPS

0.2±1.6

0.1±0.6

0.3±0.8

0.010±0.22

0.002±0.07

0.006±0.21

FFRF+GPS

0.3±1.5

0.1±1.0

0.3±0.6

-0.001±0.09 -0.001±0.04 -0.001±0.07


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Results and discussion Handover tests Oct 28th (16:30) – Oct 30th (18:30), 2010


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Conclusions and future work ¾ Sensor fusion allows the generation of relative navigation solution with increased: ¾ Robustness (tolerance to bad data points) ¾ Flexibility (single design for different mission scenarios) ¾ Reliability and availability (tolerance to measurement gaps or data outages)

¾ FFRF/GPS sensor fusion provides concepts for precise relative navigation in HEO ¾ Simple design of the relative navigation filter ¾ Feasibility of the approach ¾ Limitations in dynamical modelling and maneuver handling

¾ Integral design using measurements from GPS/FFRF/VBS sensors ¾ Generation of precise kinematic GPS measurements using PPP techniques could enable sensor fusion for real-time relative navigation


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