Comparison of Cooperative Search Algorithms for Mobile RF Targets Using Multiple Unmanned Aerial Vehicles

George W. P. York (), Daniel J. Pack () and Jens Harder
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George W. P. York: United States Air Force Academy USAF Academy
Daniel J. Pack: United States Air Force Academy USAF Academy
Jens Harder: United States Air Force Academy USAF Academy

A chapter in Cooperative Systems, 2007, pp 387-403 from Springer

Abstract: Summary In this chapter, we compare two cooperative control algorithms for multiple Unmanned Aerial Vehicles (UAVs) to search, detect, and locate multiple mobile RF (Radio Frequency) emitting ground targets. We assume the UAVs are equipped with low-precision RF direction finding sensors with no ranging capability and the targets may emit signals randomly with variable duration. In the first algorithm the UAVs search a large area cooperatively until a target is detected. Once a target is detected, each UAV uses a cost function to determine whether to continue searching to minimize overall search time or to cooperate in localization of the target, joining in a proper orbit for precise triangulation to increase localization accuracy. In the second algorithm the UAVs fly in formations of three for both search and target localization. The first algorithm minimizes the total search time, while the second algorithm minimizes the time to localize targets after detection. Both algorithms combine a set of intentional cooperative rules with individual UAV behaviors optimizing a performance criterion to search a large area. This chapter will compare the total search time and localization accuracy generated by multiple UAVs using the two algorithms simulations as we vary ratios of the numbers of UAVs to the number of targets.

Keywords: Target Localization; Unmanned Aerial Vehicle; Search Time; Global Search; Model Predictive Control (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1007/978-3-540-48271-0_23

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