电磁矢量传感器阵列相干和独立信号DOA估计

doi:10.3969/j.issn.0372-2112.2017.09.034

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电子学报 ›› 2017, Vol. 45 ›› Issue (9) : 2296-2301. DOI: 10.3969/j.issn.0372-2112.2017.09.034

科研通信

电磁矢量传感器阵列相干和独立信号DOA估计

陈广东, 黄海行, 陈智

作者信息 +

DOA Estimation with Arrays of Electromagnetic Vector Sensors Under the Coexistence of Both Uncorrelated and Coherent Signals

CHEN Guang-dong, HUANG Hai-xing, CHEN Zhi

Author information +

文章历史 +

摘要

本文研究利用矢量传感器阵列接收数据的高阶累计量区分独立和相干信号，进行参数估计.从矢量阵列信号高阶累积量任意数量的切片中估计多信号中的一个独立信号参数时，利用隔离向量选通目标信号，对其他信号进行隔离，提高了独立信号参数估计性能，信号源中可包含相干信号.独立信号的电场导向矢量与电磁导向矢量因垂直而内积为零，利用此关系可得到已虑除了所有独立信号的多个四阶累积量切片矩阵，相干信号存在于矩阵的信号子空间中.滤除独立信号估计相干信号参数，可提高相干信号参数估计性能.因可抑制任意方向，任意数量的独立干扰，即能抗饱和干扰，算法可作为电子对抗工具.仿真试验表明该方法有效.

Abstract

We study DOA(Direction Of Arrival) estimation of the independent and coherent signals with arrays of electromagnetic vector sensors.With a gating vector to select the target signal and isolate other signals,an independent signal parameter in multi-signals is estimated from multi-cumulant matrices,while other signals are suppressed.The inner product of electric and magnetic steering vectors is zero for perpendicular,which is used to filter all the independent signals in the fourth-order cumulants of the observed data.So only the coherent signals exist in the signal subspace of the cumulant matrices.The performance of multi-signals parameters estimation is improved by the separation of independent and coherent signals.Due to the suppression of any direction and number of independent interference,this algorithm has the ability to resist saturation interference and can be used as a tool for electronic warfare.The simulation experiment shows the method is stable and effective.

导出引用

陈广东, 黄海行, 陈智. 电磁矢量传感器阵列相干和独立信号DOA估计[J]. 电子学报, 2017, 45(9): 2296-2301. https://doi.org/10.3969/j.issn.0372-2112.2017.09.034

CHEN Guang-dong, HUANG Hai-xing, CHEN Zhi. DOA Estimation with Arrays of Electromagnetic Vector Sensors Under the Coexistence of Both Uncorrelated and Coherent Signals[J]. Acta Electronica Sinica, 2017, 45(9): 2296-2301. https://doi.org/10.3969/j.issn.0372-2112.2017.09.034

中图分类号： TN911.7

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