Extended Search Planning for Multiple Moving Targets Incorporating Search Priorities

Min-Hyuk Kim, Suhwan Kim, Bongkyu Han
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Abstract

This article deals with a one-searcher multi-target search problem where targets with different detection priorities move in Markov processes in each discrete time interval over a given space search area, and the total number of search time intervals is fixed. A limited search resource is available in each search time interval and an exponential detection function is assumed. The searcher can obtain a target detection reward, if the target is detected, which represents the detection priority of target and does not increase with respect to time. The objective is to establish the optimal search plan that allocates the search resource effort over the search areas in each time interval in order to maximize the total detection reward. The analysis shows that the given problem can be decomposed into interval-wise individual search problems, each being treated as a single stationary target problem for each time interval. Thus, an iterative procedure is derived to solve a sequence of stationary target problems. The computational results show that the proposed algorithm guarantees optimality.
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包含搜索优先级的多个运动目标的扩展搜索规划
本文研究了一个单搜索器多目标搜索问题,在给定的空间搜索区域中,具有不同检测优先级的目标在每个离散时间间隔内以马尔可夫过程的方式移动,并且搜索时间间隔的总数是固定的。在每个搜索时间间隔内,可用的搜索资源是有限的,并且假设一个指数检测函数。如果目标被检测到,搜索者可以获得目标检测奖励,该奖励表示目标的检测优先级,且不随时间增加。目标是建立最优的搜索计划,在每个时间间隔内将搜索资源的努力分配到搜索区域上,以使总检测奖励最大化。分析表明,给定的问题可以分解为区间独立搜索问题,每个问题在每个时间区间被视为单个平稳目标问题。因此,导出了求解一系列平稳目标问题的迭代过程。计算结果表明,该算法保证了最优性。
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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