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An improved algorithm for spatial spectrum estimation in array signal processing

机译:阵列信号处理中空间频谱估计的一种改进算法

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Direction of Arrival (DOA) estimation based on array signal processing is the main content of spatial spectrum estimation. Multiple Signal Classification (MUSIC) is the most classical super-resolution spatial spectrum estimation method. Under ideal condition, the algorithm can precisely estimate the DOA of uncorrelated signals. However, the performance of MUSIC algorithm will degrade seriously or even fail in the coherent source signal estimation. In the condition that many artificial signals have cyclostationary characteristics which use the target signal information, circular cross correlation MUSIC algorithm can further improve the quality of signal processing and have better noise suppressing property and resolution. But it is restricted to the cyclic correlation signal resolution. Therefore, this paper proposes an improved circular cross correlation MUSIC algorithm. Simulation results show that the performance of the improved circular cross correlation MUSIC algorithm is superior to the conventional MUSIC algorithm and circular cross correlation MUSIC algorithm in noise suppressing and signal selectivity.
机译:基于阵列信号处理的到达方向(DOA)估计是空间频谱估计的主要内容。多信号分类(MUSIC)是最经典的超分辨率空间频谱估计方法。在理想条件下,该算法可以精确估计不相关信号的DOA。但是,MUSIC算法的性能将严重降低,甚至在相干源信号估计中也会失败。在许多人造信号具有利用目标信号信息的循环平稳特性的情况下,圆形互相关MUSIC算法可以进一步提高信号处理的质量,并具有更好的噪声抑制性能和分辨率。但这仅限于循环相关信号的分辨率。因此,本文提出了一种改进的圆形互相关MUSIC算法。仿真结果表明,改进的圆形互相关MUSIC算法在噪声抑制和信号选择性方面优于传统的MUSIC算法和圆形互相关MUSIC算法。

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