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Cooperative Control for Target Classification

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Cooperative Control and Optimization

Part of the book series: Applied Optimization ((APOP,volume 66))

Abstract

An overview is presented of ongoing work in cooperative control for unmanned air vehicles, specifically wide area search munitions, which perform search, target classification, attack, and damage assessment. The focus of this paper is the cooperative use of multiple vehicles to maximize the probability of correct target classification. Capacitated transhipment and market based bidding are presented as two approaches to team and vehicle assigment for cooperative classification. Templates are developed and views are combined to maximize the probability of correct target classification over various aspect angles. Optimal trajectories are developed to view the targets. A false classification matrix is used to represent the probability of incorrectly classifying nontargets as targets. A hierarchical distributed decision system is presented that has three levels of decomposition: The top level performs task assignment using a market based bidding scheme; the middle subteam level coordinates cooperative tasks; and the lower level executes the elementary tasks, eg path planning. Simulations are performed for a team of eight air vehicles that show superior classification performance over that achievable when the vehicles operate independently.

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References

  1. Passino, Kevin M., Marios M. Polycarpu, David Jacques, and Meir Pachter, “Distributed Cooperation and Control for Autonomous Air Vehicles”, ibid.

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  2. Gillen, Daniel P., and David R. Jacques, “Cooperative Behavior Schemes for Improving the Effectiveness of Autonomous Wide Area Search Munitions”, ibid.

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© 2002 Kluwer Academic Publishers

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Chandler, P.R., Pachter, M., Nygard, K.E., Swaroop, D. (2002). Cooperative Control for Target Classification. In: Murphey, R., Pardalos, P.M. (eds) Cooperative Control and Optimization. Applied Optimization, vol 66. Springer, Boston, MA. https://doi.org/10.1007/0-306-47536-7_1

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  • DOI: https://doi.org/10.1007/0-306-47536-7_1

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-0549-7

  • Online ISBN: 978-0-306-47536-8

  • eBook Packages: Springer Book Archive

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