均匀混响背景下抗多目标干扰恒虚警检测器设计

殷超然; 闫林杰; 郝程鹏; 孙梦茹

doi:10.11993/j.issn.2096-3920.2019.04.011

均匀混响背景下抗多目标干扰恒虚警检测器设计

doi: 10.11993/j.issn.2096-3920.2019.04.011

1.
中国科学院声学研究所, 北京, 100190
2.
中国科学院大学电子电气与通信工程学院, 北京, 100049

基金项目: 国家自然科学基金项目资助(61571434)

详细信息

作者简介:
殷超然(1996-), 男, 在读博士, 主要研究方向为信号与信息处理.

中图分类号: TJ630.34; TN911.7
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- 被引次数: 0
出版历程
- 收稿日期: 2018-11-19
- 修回日期: 2019-05-18
- 刊出日期: 2019-08-31

Design of a Multi-Target Interference Resistant Constant False Alarm Rate Detector for Homogeneous Reverberation Background

1.
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
School of Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

摘要

摘要: 为提高恒虚警(CFAR)方法的抗多目标干扰能力, 文中提出一种能够对抗多目标干扰的新型UMCASO-CFAR检测器。该检测器的特点是分别对前后沿滑窗数据使用无偏最小方差估计(UMVE)方法和单元平均(CA)方法得到2个局部估计, 然后采用最小选择(SO)处理取二者中较小的一个作为均匀混响背景功率水平估计。在Swerling II型目标假设下, 推导出均匀混响背景下UMCASO-CFAR检测器虚警概率和检测概率的解析表达式, 证明其具有CFAR性能。进一步通过解析方法、蒙特卡洛仿真和实测数据处理三方面研究了该方法在均匀混响背景和多目标环境下的性能, 结果表明相较于现有方法, UMCASO-CFAR具有更好的抗多目标干扰的性能, 而且在均匀混响背景下具有非常小的CFAR检测损失。
- 恒虚警 /
- 检测器 /
- 无偏最小方差估计 /
- 单元平均 /
- 最小选择 /
- 多目标 /
- 抗干扰 /
- 均匀混响
Abstract: To improve the ability of constant false alarm rate(CFAR) method against interference of multiple targets, a new CFAR detector is designed. The unbiased minimum-variance estimation(UMVE) method and the cell average(CA) method are applied to the data of left and right reference windows to obtain two local estimates, and then the smaller of(SO) two is taken as the power level estimate of homogeneous reverberation background. Under the assumption of Swerling II target, the closed-form formulas of the UMCASO-CFAR detector’s false alarm probability and detection probability in homogeneous reverberation background are derived, CFAR property of the detector is proved. Further, the performances of the detector in both homogeneous background and multi-target environment are discussed by means of analytical method, Monte Carlo simulation and measured data processing. The results show that compared with the existing methods, the UMCASO-CFAR detector has higher capability to resist mul-ti-target interference, and ensures a very small CFAR detection loss in homogeneous reverberation background.
- constant false alarm rate(CFAR) /
- detector /
- unbiased minimum-variance estimation(UMVE) /
- cell-ave- rage(CA) /
- small of(SO) /
- multi-target /
- interference resistant /
- homogeneous reverberation

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参考文献(16)

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