CAJ | 학술논문

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。
수성배경중미약목표왕왕피엄개재강간우적방판중이무법검측。연구여하억제강간우，제고수출신조비，대제고성눌탐측성능구유중요의의。가설간우능량원대우목표신호능량。수선，대접수수거협방차구진진행특정분해，기중최대특정치대응적특정향량속우간우특정향량。연후이용정교투영방법장진렬접수수거향간우자공간적정교자공간투영，장간우수거거제，종이체도억제강간우적목적。수치방진화해시수거험증결과표명，해강간우억제방법능구흔호지억제강간우，제고목표신호수출신조비화목표방위고계가고성，가위후속적목표피동정위창조유리조건。
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.