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随着声呐检测能力的提高,多目标干扰下微弱信号的检测问题日益突出。当声呐方位历程显示上出现多个干扰轨迹时,弱目标的检测显得十分困难。自适应噪声抵消(Adaptive Noise Canceling,ANC)技术为抑制多个干扰提供了理论基础,但是求解稳态最佳滤波矩阵存在着技术实现上的困难。本文提出用一种反波束成形(Inverse Beamforming,IBF)递推算法,在阵元域逐一抵消多个强干扰,从而增强并提取出微弱目标信号。文中给出了递推求解由逆矩阵所表达的最佳滤波矢量的理论推导和相应的公式。利用IBF算法处理海试数据得到了较好的结果,显著改善了强干扰下对微弱信号的检测,甚至在普通波束成形(CBF)中未能显示出来的信号都可以被检测出来。
With the improvement of sonar detection capability, the detection of weak signals under multi-target interference has become increasingly prominent. When the sonar azimuth shows multiple interference trajectories, the detection of weak targets is very difficult. Adaptive Noise Canceling (ANC) provides a theoretical basis for suppressing multiple interferences, but there are technical difficulties in solving the steady-state optimal filtering matrix. In this paper, an inverse beamforming (IBF) recursive algorithm is proposed to cancel out multiple strong interferences one by one in the array element domain to enhance and extract weak target signals. In this paper, the theoretical derivation and corresponding formulas of recursive solution of the best filter vector expressed by inverse matrix are given. The IBF algorithm is used to process the sea-trial data to obtain good results, which significantly improves the detection of weak signals under strong interference. Even the signals that can not be displayed in normal beamforming (CBF) can be detected.