An extended time horizon search technique for cooperative unmanned vehicles to locate mobile RF targets

D. Pack, G. York
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引用次数: 6

Abstract

In this paper, we present a behavior-based, distributed, cooperative search algorithm for multiple unmanned aerial vehicles (UAVs) to cooperatively find sub-optimal search patterns to detect moving radio frequency (RF) signal emitting targets. The overall goal of the search algorithm is to compute sub-optimal flight trajectories for participating UAVs to minimize the combined search cost: search coverage, time, fuel usage, and communication overhead. The focus for this paper is to extend our existing search algorithm 's ability to incorporate evaluations of flight path options beyond the immediate time horizon. The paper explores the trade-offs over the additional computation cost and the reduction of the total search time. In addition to finding a set of sub-optimal UAV search paths, the search algorithm also generates a priority list of possible, search paths. The list is then used by an individual UAV to adjust its path selection to minimize a global search cost. Collectively, the selected UAV paths produce sub-optimal search patterns for a group of UAVs. The validity of the search algorithm is demonstrated using computer simulation
协同无人车移动射频目标定位的扩展时间范围搜索技术
本文提出了一种基于行为的分布式协同搜索算法,用于多架无人机协同寻找次优搜索模式,以检测移动射频信号发射目标。搜索算法的总体目标是计算参与无人机的次优飞行轨迹,以最小化联合搜索成本:搜索覆盖范围、时间、燃料使用和通信开销。本文的重点是扩展我们现有的搜索算法的能力,以纳入超越当前时间范围的飞行路径选择的评估。本文探讨了在额外的计算成本和减少总搜索时间之间的权衡。除了找到一组次优无人机搜索路径外,搜索算法还生成一个可能搜索路径的优先级列表。然后,单个无人机使用该列表来调整其路径选择,以最小化全局搜索成本。总的来说,所选择的无人机路径产生一组无人机的次优搜索模式。通过计算机仿真验证了该搜索算法的有效性
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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