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Proceedings Paper

Space collision threat mitigation
Author(s): Aleksandar Zatezalo; Dušan Stipanović; Raman K. Mehra; Khanh Pham
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Paper Abstract

Mitigation of possible collision threats to current and future operations in space environments is an important an challenging task considering high nonlinearity of orbital dynamics and discrete measurement updates. Such discrete observations are relatively scarce with respect to space dynamics including possible unintentional or intentional rocket propulsion based maneuvers even in scenarios when measurement collections are focused to a one single target of interest. In our paper, this problem is addressed in terms of multihypothesis and multimodel estimation in conjunction with multi-agent multigoal game theoretic guaranteed evasion strategies. Collision threat estimation is formulated using conditional probabilities of time dependent hypotheses and spacecraft controls which are computed using Liapunov-like approach. Based on this formulation, time dependent functional forms of multi-objective utility functions are derived given threat collision risk levels. For demonstrating developed concepts, numerical methods are developed using nonlinear filtering methodology for updating hypothesis sets and corresponding conditional probabilities. Space platform associated sensor resources are managed using previously developed and demonstrated information-theoretic objective functions and optimization methods. Consequently, estimation and numerical methods are evaluated and demonstrated on a realistic Low Earth Orbit collision encounter.

Paper Details

Date Published: 20 June 2014
PDF: 13 pages
Proc. SPIE 9091, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII, 90910H (20 June 2014); doi: 10.1117/12.2050663
Show Author Affiliations
Aleksandar Zatezalo, Scientific Systems Co., Inc. (United States)
Dušan Stipanović, Univ. of Illinois at Urbana-Champaign (United States)
Raman K. Mehra, Scientific Systems Co., Inc. (United States)
Khanh Pham, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 9091:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII
Ivan Kadar, Editor(s)

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