Astrometric and photometric data fusion for resident space object orbit, attitude, and shape determination via multiple-model adaptive estimation

Richard Linares, John L. Crassidis, Moriba K. Jah, Hakjae Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Scopus citations

Abstract

This paper presents a new method, based on a multiple-model adaptive estimation approach, to determine the most probable shape of a spacecraft in orbit among a number of candidate shape models while simultaneously recovering the observed resident space object's inertial orientation and trajectory. Multiple-model adaptive estimation uses a parallel bank of filters to provide multiple resident space object state estimates, where each filter is purposefully dependent on a mutually unique resident space object model. Estimates on the conditional probability of each model given the available measurements are provided from the multiple-model adaptive estimation approach. Each filter employs the Unscented (or Sigma-Point) estimation approach, reducing passively-collected electro-optical data to infer the unknown state vector comprised of the resident space object inertial-to-body orientation, position and their respective temporal rates. Each hypothesized model results in a different observed optical cross-sectional area. The effect of solar radiation pressure may be recovered from accurate angles-data alone, if the collected measurements span a sufficiently long period of time so as to make the non-conservative mismodeling effects noticeable. However, for relatively short data arcs, this effect is weak and thus the temporal brightness of the resident space object can be used in concert with the angles data to exploit the fused sensitivity to both resident space object characteristics and associated trajectory, the very same ones which drive the non-conservative dynamic effects. Recovering these characteristics and trajectories with sufficient accuracy is shown in this paper, where the characteristics are inherent in unique resident space object models. The performance of this strategy is demonstrated via simulated scenarios.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference
DOIs
StatePublished - 2010
EventAIAA Guidance, Navigation, and Control Conference - Toronto, ON, Canada
Duration: Aug 2 2010Aug 5 2010

Publication series

NameAIAA Guidance, Navigation, and Control Conference

Other

OtherAIAA Guidance, Navigation, and Control Conference
CountryCanada
CityToronto, ON
Period8/2/108/5/10

Bibliographical note

Funding Information:
This work was supported through multiple funding mechanisms, one of which was via the Air Force Research Laboratory, Space Vehicles Directorate (ASTRIA and Space Scholars program). The authors wish to thank Frank J. Centinello III for his work with Dr. Jah to further the research in light curve and angles data fusion.

Fingerprint Dive into the research topics of 'Astrometric and photometric data fusion for resident space object orbit, attitude, and shape determination via multiple-model adaptive estimation'. Together they form a unique fingerprint.

Cite this