文章摘要
金燕利,章伟裕,陈艳丽.一种基于特征分析的强干扰抑制方法[J].声学技术,2014,33(5):469~472
一种基于特征分析的强干扰抑制方法
A method of suppressing strong interference based on eigenanalysis
投稿时间:2013-07-22  修订日期:2013-11-17
DOI:10.3969/j.issn1000-3630.2014.05.016
中文关键词: 特征分解  正交投影  干扰抑制
英文关键词: eigen-decomposition  orthogonal projection  interference suppression
基金项目:
作者单位E-mail
金燕利 海军驻沈阳地区电子系统军事代表室, 辽宁沈阳 110003 zwy@mail.ioa.ac.cn 
章伟裕 中国科学院声学研究所声场声信息国家重点实验室, 北京 100190
中国科学院大学, 北京 100049 
 
陈艳丽 中国科学院声学研究所声场声信息国家重点实验室, 北京 100190
中国科学院大学, 北京 100049 
 
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中文摘要:
      水声环境中微弱目标往往被掩盖在强干扰的旁瓣中而无法检测。研究如何抑制强干扰,提高输出信噪比,对提高声呐探测性能具有重要意义。假设干扰能量远大于目标信号能量。首先,对接收数据协方差矩阵进行特征分解,其中最大特征值对应的特征向量属于干扰特征向量。然后利用正交投影方法将阵列接收数据向干扰子空间的正交子空间投影,将干扰数据去除,从而达到抑制强干扰的目的。数值仿真和海试数据验证结果表明,该强干扰抑制方法能够很好地抑制强干扰,提高目标信号输出信噪比和目标方位估计可靠性,可为后续的目标被动定位创造有利条件。
英文摘要:
      In shallow water environment, weak targets are always masked in the sidelobes of strong interference, thus the targets can not be detected. Studying how to suppress the strong interference and increase the output signal-to-noise ratio (SNR) is especially significant for improving the detection performance of sonar. In this paper, it is assumed that the interference energy is far greater than that of the target. Firstly, the eigen-decomposition of received data covariance matrix is made, and the eigenvector, which corresponds to the largest eigenvalue, is considered as the interference's ei-genvector. Then the array received data are projected to the orthogonal subspace of interference subspace by using the orthogonal projection method. The data of interference is removed so that the purpose of suppressing strong interference can be achieved. Numerical simulation and experimental results show that this method can effectively suppress the strong interference, increase the output SNR, and enhance the reliability of directions of arrival (DOA) estimates of the targets. The performance of passive ranging will be possibly improved in this condition.
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