一种基于组合子阵协方差矩阵的阵列扩展方法

doi:10.12382/bgxb.2022.1076

摘要/Abstract

摘要：

针对阵列在低信噪比条件下信号检测概率低且方位估计性能下降的问题,提出一种基于组合子阵协方差矩阵的线列阵扩展方法。该方法将阵列划分为奇偶子阵,根据子阵的互协方差与自协方差矩阵构建扩展接收数据,对扩展接收数据进行组合作为最终的阵列接收数据进行处理,由此在突破阵列物理孔径的基础上避免仅使用奇偶阵元互协方差重构接收数据时产生的栅瓣问题。仿真结果表明:新方法可以降低波束输出的旁瓣,具有较好的弱目标检测能力和方位分辨力;相比于基于奇偶阵元互协方差的阵列扩展方法,新方法可有效提升方位估计精度,且不存在栅瓣问题。

关键词: 阵列扩展, 弱目标检测, 波达方向估计, 栅瓣, 协方差矩阵

Abstract:

A linear array extension method based on combination of sub-array covariance matrices is proposed to solve the problem of performance deterioration of signal detection and azimuth estimation under low signal-to-noise ratio. The proposed method divides the array into odd and even sub-arrays, and the extended received data is constructed by using the cross-covariance and auto-covariance matrices of the two sub-arrays. Finally, the final extended signal is obtained by combining the extended received data. The proposed method breaks through the physical aperture of array, and avoids the problem of grating lobe when using the cross-covariance of odd and even sub-arrays only to reconstruct the received data. Simulated results show that the proposed method can be used to reduce the sidelobe of beam output, and has good weak target detection ability and azimuth resolution. Compared with the array extension algorithm based on the cross covariance of odd and even sub-arrays, the proposed method can provide higher azimuth estimation accuracy.

Key words: array extension, weak target detection, direction-of-arrival estimation, grating lobe, covariance matrix

中图分类号:

TN911.23

梁国龙, 罗钧戈, 郝宇, 付进. 一种基于组合子阵协方差矩阵的阵列扩展方法[J]. 兵工学报, 2024, 45(5): 1717-1724.

LIANG Guolong, LUO Junge, HAO Yu, FU Jin. An Array Extension Method Based on Combination of Sub-array Covariance Matrices[J]. Acta Armamentarii, 2024, 45(5): 1717-1724.

图/表 13

图1 线列阵结构

Fig.1 Linear array structure

图2 阵元扩展示意图

Fig.2 Schematic diagram of array element expansion

图3 扩展信号对应的阵元

Fig.3 Array element corresponding to the extended signal

图4 组合信号对应的阵元

Fig.4 Array element corresponding to the combined signal

图5 不同方法的方位谱

Fig.5 Azimuth spectrum of different methods

图6 检测概率与SNR的关系

Fig.6 Relationship between detection probability and SNR

图7 RMSE与SNR的关系

Fig.7 Relationship between RMSE and SNR

图8 方位估计误差与SNR的关系

Fig.8 Relationship between DOA estimation error and SNR

图9 分辨概率与SNR的关系

Fig.9 Relation between discrimination probability and SNR

图10 阵元位置误差对检测概率的影响

Fig.10 Influence of array element position on detection probability

图11 不同扩展信号组合下的检测概率

Fig.11 Detection probabilities under different extended signal combinations

图12 文献[2]中奇偶子阵扩展方法的方位历程图

Fig.12 Azimuth-time recording of the algorithm in Ref.[2]

图13 本文方法的方位历程图

Fig.13 Azimuth-time recording of the proposed method

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