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Sensor Scheduling for Space Object Tracking and Collision Alert

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Dynamics of Information Systems: Mathematical Foundations

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 20))

Abstract

Given the increasingly dense environment in both low-earth orbit (LEO) and geostationary orbit (GEO), a sudden change in the trajectory of any existing resident space object (RSO) may cause potential collision damage to space assets. With a constellation of EO/IR sensor platforms and ground radar surveillance systems, it is important to design optimal estimation algorithm for updating nonlinear object states and allocating sensing resources to effectively avoid collisions among many RSOs. We consider N space objects being observed by M sensors whose task is to provide the minimum mean square estimation error of the overall system subject to the cost associated with each measurement. To simplify the analysis, we assume that sensors can switch between objects instantaneously subject to additional resource and sensing geometry constraints. We first formulate the sensor scheduling problem using the optimal control formalism and then derive a tractable relaxation of the original optimization problem, which provides a lower bound on the achievable performance. We propose an open-loop periodic switching policy whose performance can approach the theoretical lower bound closely. We also discuss a special case of identical sensors and derive an index policy that coincides with the general solution to restless multi-armed bandit problem by Whittle. Finally, we demonstrate the effectiveness of the resulting sensor management scheme for space situational awareness using a realistic space object tracking simulator with both unintentional and intentional maneuvers by RSOs that may lead to collision. Our sensor scheduling scheme outperforms the conventional information gain and covariance control based schemes in the overall tracking accuracy as well as making earlier declaration of collision events.

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Acknowledgment

H. Chen was supported in part by ARO through grant W911NF- 08-1-0409, ONR-DEPSCoR through grant N00014-09-1-1169 and Office of Research & Sponsored Programs at University of New Orleans. The authors are grateful to the anonymous reviewers for their constructive comments to an earlier draft of this work.

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Authors and Affiliations

  1. Department of Electrical Engineering, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA, 70148, USA

    Huimin Chen

  2. I-Fusion Technology, Inc., 14163 Furlong Way, Germantown, MD, 20874, USA

    Dan Shen & Genshe Chen

  3. AFRL/RVSV, Bernalillo, NM, 87117, USA

    Khanh Pham

Authors
  1. Huimin Chen
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  2. Dan Shen
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  3. Genshe Chen
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  4. Khanh Pham
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Corresponding author

Correspondence to Khanh Pham .

Editor information

Editors and Affiliations

  1. , Industrial and Systems Engineering, University of Florida, Weil Hall 303, Gainesville, 32611, Florida, USA

    Alexey Sorokin

  2. Munitions Directorate, AFRL, GNC Branch, W. Eglin Blvd 101, Eglin AFB, 32542, Florida, USA

    Robert Murphey

  3. Dept. Computer & Information Science &, Engineering (CISE), University of Florida, E450, CSE Building, Gainesville, 32611, Florida, USA

    My T. Thai

  4. , Department of Industrial and Systems Eng, University of Florida, Weil Hall 401, Gainesville, 32611, Florida, USA

    Panos M. Pardalos

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Chen, H., Shen, D., Chen, G., Pham, K. (2012). Sensor Scheduling for Space Object Tracking and Collision Alert. In: Sorokin, A., Murphey, R., Thai, M., Pardalos, P. (eds) Dynamics of Information Systems: Mathematical Foundations. Springer Proceedings in Mathematics & Statistics, vol 20. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3906-6_9

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