掌握多传感器搜索目标躲避策略

D. DelBalzo, K.P. Hemsteter
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引用次数: 9

摘要

针对复杂环境下声纳搜索模式的基本优化问题,提出了基于遗传距离的搜索规划算法(GRASP)。标准场景是针对随机巡逻的威胁,最大化多个反潜战搜索器的累积检测概率(CDP)。算法的改进允许目标反探测主动声纳脉冲并机动远离搜索器。一般情况下,由于反探测距离通常大于探测距离,规避机动会大大降低CDP。该分析涵盖了人工环境中平台和传感器的几种组合。GRASP解决方案显示出显著的优势,特别是针对逃避目标。与非联合战术相比,GRASP联合战术利用目标规避机动显著提高了探测性能。一个有点令人惊讶的结果是,随着目标躲避距离的增加(更好的拦截接收器),多传感器CDP以一种可以解释的方式增加。介绍了多平台、多传感器反潜战搜索方案在提高性能和缩短搜索时间方面的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GRASP multi-sensor search tactics against evading targets
GRASP (Genetic Range-dependent Algorithm for Search Planning) was developed to nearly optimize sonar search patterns in complicated environments. The standard scenario is to maximize cumulative detection probability (CDP) for several ASW searchers against a randomly patrolling threat. An improvement to the algorithms allows the target to counter-detect an active sonar pulse and to maneuver away from the searcher. In general, the CDP is reduced dramatically by evasive maneuvers, since the counter-detection range is usually greater than the detection range. The analysis covers several combinations of platforms and sensors in artificial environments. The GRASP solutions show significant benefit, especially against an evading target. GRASP joint tactics exploit target evasive maneuvers to significantly increase detection performance relative to non-joint tactics. A somewhat surprising result is that as the target evasion range increases (better intercept receiver), the multi-sensor CDP increases in an explainable way. The advantages of multi-platform and multisensor ASW search plans are described in terms of improved performance and reduced search time.
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