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Framework for low-observable trajectory generation in presence of multiple radars

Inanc, Tamer and Muezzinoglu, Mehmet K. and Misovec, Kathleen and Murray, Richard M. (2008) Framework for low-observable trajectory generation in presence of multiple radars. Journal of Guidance, Control, and Dynamics, 31 (6). pp. 1740-1749. ISSN 0731-5090. doi:10.2514/1.35287.

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This paper explores the problem of finding a real-time optimal trajectory for unmanned aerial vehicles to minimize their probability of detection by opponent multiple radar detection systems. The problem is handled using the nonlinear trajectory generation method developed by Milam et al. (Milam, M., Mushambi, K., and Murray, R., "New Computational Approach to Real-Time Trajectory Generation for Constrained Mechanical Systems," Proceedings of the 39th IEEE Conference on Decision and Control, Vol. 1, Institute of Electrical and Electronics Engineers, New York, Dec. 2000, pp. 845-851.) The paper presents a formulation of the trajectory generation task as an optimal control problem, where temporal constraints allow periods of high observability interspersed with periods of low observability. This feature can be used strategically to aid in avoiding detection by an opponent radar. The guidance is provided in the form of sampled tabular data. It is then shown that the success of nonlinear trajectory generation on the proposed low-observable trajectory generation problem depends upon an accurate parameterization of the guidance data. In particular, such an approximator is desired to have a compact architecture, a minimum number of design parameters, and a smooth continuously differentiable input-output mapping. Artificial neural networks as universal approximators are known to possess these features, and thus are considered here as appropriate candidates for this task. Comparison of artificial neural networks against B-spline approximators is provided, as well. Numerical simulations on multiple radar scenarios illustrate unmanned air vehicle trajectories optimized for both detectability and time.

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Murray, Richard M.0000-0002-5785-7481
Additional Information:© 2008 American Institute of Aeronautics and Astronautics, Inc. Received 24 October 2007; revision received 15 January 2008; accepted for publication 7 February 2008. This research is based upon work supported by the Defense Advanced Research Projects Agency Advanced Research Projects, Information Exploitation Office, and the U.S. Air Force Research Laboratory under Contract No. F33615-01-C-3149. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Defense Advanced Research Projects Agency or the U.S. Air Force. The authors gratefully acknowledge the helpful comments of the reviewers as well as the Defense Advanced Research Projects Agency and U.S. Air Force Research Laboratory management.
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Defense Advanced Research Projects AgencyUNSPECIFIED
Air Force Research LaboratoryF33615-01-C-3149
Issue or Number:6
Record Number:CaltechAUTHORS:INAjgcd08
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:13536
Deposited By: Tony Diaz
Deposited On:13 Aug 2009 21:35
Last Modified:08 Nov 2021 22:38

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