多基地声呐融合探测关键技术研究

张浩宇; 韩一娜; 赵伟康; 杨益新; 刘清宇

doi:10.11993/j.issn.2096-3920.2018.05.013

多基地声呐融合探测关键技术研究

doi: 10.11993/j.issn.2096-3920.2018.05.013

1.
西北工业大学航海学院, 陕西西安, 710072
2.
海军研究院, 北京, 100073

基金项目: 国家重点研发计划(2016YFC1400200),国家自然科学基金面上项目(61671388)

详细信息

作者简介:
张浩宇(1995-), 男, 在读硕士, 主要研究方向为多基地融合跟踪.

中图分类号: TJ630.34; TB566; TP181
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- 文章访问数: 677
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- 被引次数: 0
出版历程
- 收稿日期: 2018-08-06
- 修回日期: 2018-09-29
- 刊出日期: 2018-10-31

Key Technologies of Multistatic Sonar Fusion Detection

1.
School of Marine and Technology, Northwestern Polytechnical University, Xi′an 710068, China
2.
Naval Research Academy, Beijing 100073, China

摘要

摘要: 为了解决多基地声呐中的融合探测问题, 文中分别探讨了多基地声呐融合探测中的测量模型、数据关联和跟踪器性能模型3个关键技术。测量模型包括时间、方位、位置和声速的误差分布和目标的定位表达式, 给出了各个误差因素的表达式和定位误差的表达式。数据关联用来解决得到的测量与已知目标之间的分配问题, 重点介绍了最近邻数据关联和多假设数据关联方法, 这2种方法使用相同的数据模型、测量模型和运动模型, 通过对最近邻数据关联和多假设数据关联进行仿真, 发现均能对目标实现良好的跟踪。跟踪器性能模型用来评估跟踪器输出质量, 分别从跟踪检测概率、跟踪碎片和错误跟踪率3个性能指标评估输出质量, 通过仿真得到的性能指标可知, 多假设数据关联跟踪器的输出质量明显优于最近邻数据关联跟踪器的输出质量。
- 多基地声呐 /
- 测量模型 /
- 数据关联 /
- 跟踪器性能模型
Abstract: To solve the fusion detection problem for multistatic sonar, this paper discusses three key technologies, i.e., measurement model, data association, and tracker performance model. The measurement model includes the error distributions of time, azimuth, position and sound velocity, as well as the localization expression of a target. The expression of each error factor and the expression of localization error are given. Data association is an important part of fusion detection to solve the assignment problem between measurements and known targets. The methods of nearest neighbor data association and multiple hypothesis data association are introduced in detail. The two data association methods use the same data model, measurement model and motion model. Simulations on the nearest neighbor data association and multiple hypothesis data association show that the target can be well tracked. The tracker performance model is used to evaluate the output quality of the tracker. The output quality is evaluated according to three performance parameters, i.e., tracking probability of detection, tracking fragmentation, and false alarm rate if tracking. According to the performance parameters from simulation, the output quality of the multiple hypothesis data association tracker is significantly better than that of the nearest neighbor data association tracker.
- multistatic sonar /
- measurement model /
- data association /
- tracker performance model

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参考文献(10)

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