基于海试数据分析的潜水探测声纳自动目标跟踪算法性能分析

H. Lee, Sung-Chur Kwon, W. Oh, K. Shin
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引用次数: 0

摘要

本文讨论了用于监测沿海军事设施和重大基础设施突防力的潜水探测声纳自动目标跟踪算法。首先,分析了潜水员探测声纳的海试数据,构建了基于航迹存在概率作为杂波环境下航迹质量度量的目标自动跟踪算法。重点介绍了航迹管理算法,包括航迹起始、确认、终止、合并和目标跟踪算法,其中包括单目标跟踪IPDAF(集成概率数据关联滤波器)和多目标跟踪LMIPDAF(线性多目标集成概率数据关联滤波器)。利用海试数据和蒙特卡罗仿真数据分析了自动目标跟踪算法的性能。
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Performance analysis of automatic target tracking algorithms based on analysis of sea trial data in diver detection sonar
In this paper, we discussed automatic target tracking algorithms for diver detection sonar that observes penetration forces of coastal military installations and major infrastructures. First of all, we analyzed sea trial data in diver detection sonar and composed automatic target tracking algorithms based on track existence probability as track quality measure in clutter environment. In particular, these are presented track management algorithms which include track initiation, confirmation, termination, merging and target tracking algorithms which include single target tracking IPDAF (Integrated Probabilistic Data Association Filter) and multitarget tracking LMIPDAF (Linear Multi-target Integrated Probabilistic Data Association Filter). And we analyzed performances of automatic target tracking algorithms using sea trial data and monte carlo simulation data.
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CiteScore
0.60
自引率
50.00%
发文量
1
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