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一种稳健的零陷扩展算法 被引量:1

Robust Broadening Null Width Algorithm
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摘要 协方差矩阵求逆算法具有在强干扰条件下提取弱期望的优良性能。但算法受幅相误差影响明显,且干扰方向处的零陷宽度很窄,当干扰方向变化时会导致抑制干扰能力下降。文章利用快速测向给出的信号示向度,运用最大似然迭代估计出各信源对应方向的实际方向向量值。再利用导数约束条件对协方差矩阵求逆算法的目标函数进行约束,从而使零陷宽度得以扩展且鲁棒性增强。仿真实验验证了算法的有效性。 Stimulate covariance Matrix Inversing has perfect performance in picking up low powerful desire signal restraining strong powerful interferences. However, Performance will deteriorate greatly when amplitude or phase error exists. Furthermore, width of the null is very narrow. For the moving interference, performance will also deteriorate. Using DOA information which is got from fast DOA finding method, we get the estimations of real steering vectors by maximum likelihood iterative algorithm. Then put derivative constraints on all the interference directions to make the corresponding null more flat. Large numbers of simulations are provided to demonstrate the effectiveness of the proposed algorithm.
作者 刘磊 尹海昌
出处 《信息工程大学学报》 2008年第3期331-333,338,共4页 Journal of Information Engineering University
关键词 稳健性 零限展宽 方向估计 robustness broadening null width direction of estimation
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