Enabling distributed spacecraft system operations with the crosslink transceiver

Stadter, P.A.; Chacos, A.A.; Heins, Robert J.; Asher, M.S.

doi:10.1109/aero.2002.1035618

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Other formation flying navigation research has focused on augmenting GPS measurements with local ranging devices [25,26,27,28,29]. While useful for extending fleet estimation beyond LEO, the nonlinear measurements, by definition, couple the state estimates of each vehicle, complicating the algorithmic decentralization possible in Ref.…”

Section: Existing Technologiesmentioning

confidence: 99%

“…Thus, a measurement augmentation is desired to permit estimation through these spells of invisibility and also to improve estimation accuracy when the NAVSTAR constellation is visible. [25,26,27,28,29]. Unfortunately, however, the local range measurements taken by each vehicle by definition strongly correlate the states of each vehicle, thus making the full fleet measurement matrix, H, no longer blockdiagonal and non-trivial to decentralize [50].…”

Section: Chaptermentioning

confidence: 99%

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Decentralized Estimation Algorithms for Formation Flying Spacecraft

Ferguson

How

2003

AIAA Guidance, Navigation, and Control Conference and Exhibit

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Many future space missions, such as space-based radar, earth mapping, and interferometry, will require formation flying of multiple spacecraft to achieve their very advanced science objectives. While formation flying offers many performance and operational advantages, there are several challenges that must be addressed, including navigation, control, autonomy, distributed data management, efficient inter-vehicle communication, and robustness. One of the key issues with formation flying of large fleets is selecting the overall system architecture, because it drives the distribution of the various algorithms and the extent to which data must be transmitted.These challenges are particularly evident with the relative navigation. While carrier-phase differential GPS can be used as a highly accurate sensor for LEO formations, it is not sufficient as the sole sensor for missions beyond LEO. If local ranges and range rates are used to augment or replace the GPS measurements, precise estimation can continue into MEO and beyond. However these new measurements complicate the estimator decentralization by coupling the vehicles' state estimates.This thesis explores solutions to many of these challenges within the context of the Orion microsatellite formation flying mission. It also presents the Formation Flying Information Technology testbed, developed to evaluate the communication and computational requirements associated with various system architectures when using augmented GPS. Several architectures and their associated estimation algorithms are also analyzed and compared in terms of performance, computation, and communication requirements. This analysis clearly shows that the decentralized reduced-order filters provide near optimal estimation without excessive communication or computation requirements. Embedding these reduced-order estimators within the hierarchic architecture presented should also permit scaling of the relative navigation to very large fleets. AcknowledgmentsIn carrying out the research that went into this Master's thesis, there were several key individuals that played large roles in helping me make it to the end. This was a long and difficult road at times and I thank everyone whole-heartedly for their kindness and support over the past two years.Firstly, I would like to thank my advisor, Professor Jonathan P. How for directing and guiding me through this research. Professor How's strong will and drive for excellence kept me on track, studying new and exciting topics along the way. Professor How taught me the keys to effective research, and for that, I thank him.

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Section: Existing Technologiesmentioning

confidence: 99%

Section: Chaptermentioning

confidence: 99%

Decentralized Estimation Algorithms for Formation Flying Spacecraft

Ferguson

How

2003

AIAA Guidance, Navigation, and Control Conference and Exhibit

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“…Thus, a measurement augmentation is desired to permit relative navigation through periods of poor visibility and also to improve the accuracy when the GPS constellation is visible. 5,6,7,8,9 However, the local range measurements taken onboard the spacecraft strongly correlate the states of the vehicles, which destroys the block-diagonal nature of the fleet measurement matrix 4,10 and greatly complicates the process of decentralizing the algorithms. 12 In contrast to the GPS-only estimation scenario, which effectively decentralizes for reasonable fleet separations, this estimation problem does not decorrelate at any level.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Decentralized Estimation Filters for Formation Flying Spacecraft

Mandić

Breger

How

2004

AIAA Guidance, Navigation, and Control Conference and Exhibit

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Future formation flying missions are being planned for fleets of spacecraft in MEO, GEO, and beyond where relative navigation using GPS will either be impossible or insufficient. To perform fleet estimation for these scenarios, local ranging devices on each vehicle are being considered to replace or augment the available GPS measurements. A previous paper presented several approaches for distributing the computational load of the estimation process across the vehicles in the fleet. This paper extends the previous work to present a more detailed investigation of the covariances for the different distributed estimation algorithms. This enables an analysis of the transient effects as the ranging measurements are added to the estimator, which extends the previous steady-state comparison. This transient covariance analysis more clearly shows the effect of ignoring errors in the ranging measurements that result when the location of the target vehicle is also not well known. These results provide further insight on the relative performance of these filters and identifies the Schmidt covariance correction (SCC), the essence of the Schmidt Kalman Filter, as being responsible for better performance of Schmidt Kalman Filter compared to other decentralized filters.

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