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Improved algorithm of mainlobe interference suppression based on eigen-subspace

机译:基于特征子空间的主瓣干扰抑制改进算法

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When there is only the mainlobe interference signal, the algorithm of mainlobe interference suppression based on eigen-projection matrix preprocessing (EMP) has stronger robustness than that based on blocking matrix preprocessing (BMP). However, when the mainlobe interference signal and sidelobe interference signal are simultaneously present and the mainlobe interference signal's power is close to the sidelobe interference signal's power, the null steering direction's gain of sidelobe interference signal will be increasing. It decreases the performance of EMP algorithm. To solve these problems, an improved algorithm of the mainlobe interference suppression based on eigen-subspace is proposed to deal with the problem of the null steering reduction in the sidelobe interference in the case of high mainlobe interference-to-noise-ratio. Simulation results have shown that the proposed algorithm has good robustness which can effectively suppress the mainlobe interference and maintain the deep null steering in the direction of sidelobe interference signal in the array pattern, in the case of the different mainlobe interference-to-noise-ratio.
机译:当仅存在主瓣干扰信号时,基于特征投影矩阵预处理(EMP)的主瓣干扰抑制算法比基于块矩阵预处理(BMP)的算法具有更强的鲁棒性。然而,当同时存在主瓣干扰信号和旁瓣干扰信号并且主瓣干扰信号的功率接近旁瓣干扰信号的功率时,旁瓣干扰信号的零方向的增益将增加。它降低了EMP算法的性能。为了解决这些问题,提出了一种基于特征子空间的改进的主瓣干扰抑制算法,以解决主瓣干扰与噪声比高的情况下,旁瓣干扰的空导减小的问题。仿真结果表明,该算法具有良好的鲁棒性,在不同主瓣干扰噪声比的情况下,可以有效抑制主瓣干扰,并在阵列模式下保持旁瓣干扰信号方向的深空导引。 。

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