混响背景下基于高阶统计量的动目标检测方法
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作者单位:

(海军工程大学 电子工程学院, 湖北 武汉 430033)

作者简介:

王晓彤(1991—),女,山东青岛人,博士研究生,E-mail:wxtouc@163.com; 蔡志明(通信作者),男,教授,博士,博士生导师,E-mail:caizm2008@sina.com

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中图分类号:

TN911.7

基金项目:

国家自然科学基金资助项目(41506118,51679247)


Moving target detection method of reverberation background based on high-order statistics
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Affiliation:

(College of Electronic Engineering, Naval University of Engineering, Wuhan 430033, China)

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    摘要:

    针对混响背景中的动目标检测问题,根据基阵接收数据经过波束形成与匹配滤波后的输出结果计算高阶统计量,并将其视作观测空间。基于此空间中混响和目标回波的差异,利用多ping的高阶统计量构造特征向量,计算特征向量之间的马氏距离作为混响和目标差异的量化标准,再依据最大一致条件功效检测准则选择门限检测方法。波形数据仿真与海上实录数据检验均表明该方法的检测性能优于单ping波束形成及匹配滤波方法。通过蒙特卡洛仿真获得不同信混比下的接收机工作特性曲线,与单ping检测相比,在保证虚警概率小于0.01、检测概率大于0.5的条件下,最小可检测信混比降低约6 dB。

    Abstract:

    Considering the moving target detection in reverberation background, the high-order statistics obtained by the output of received data after beamforming and matched filtering were regarded as statistical observation space. Based on the high-order statistical characteristic difference of reverberation and target echoes, the high-order statistics can be used to build characteristic vectors by multiple ping output. The Mahalanobis distance between characteristic vectors of the target and reverberation was used as the quantified standard to measure difference between the target and reverberation. The threshold was based on the maximal constant conditional power test. ROC(receiver operating characteristic) curves were obtained under different signal-reverberation ratio conditions by Monte Carlo simulations. Simulations and sea trial results show that the new method achieves higher performance than traditional detection using single ping.The output signal-reverberation ratio, which ensures the false alarm lower than 0.01 and the detection probability higher than 0.5, is reduced to 3 dB, approximately 6 dB less than that of the traditional method.

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王晓彤,蔡志明.混响背景下基于高阶统计量的动目标检测方法. Moving target detection method of reverberation background based on high-order statistics[J].国防科技大学学报,2020,42(2):135-141.

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  • 收稿日期:2018-11-06
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  • 在线发布日期: 2020-04-29
  • 出版日期: 2020-04-28
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