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一种基于协方差矩阵的增强平滑范数波达方向估计方法

An Enhanced Smoothed -Norm Direction of Arrival Estimation Method Using Covariance Matrix.

作者信息

Paik Ji Woong, Lee Joon-Ho, Hong Wooyoung

机构信息

Radar System Team 2, Hanwha Systems, Yongin-City 17121, Korea.

Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea.

出版信息

Sensors (Basel). 2021 Jun 27;21(13):4403. doi: 10.3390/s21134403.

Abstract

An enhanced smoothed l0-norm algorithm for the passive phased array system, which uses the covariance matrix of the received signal, is proposed in this paper. The SL0 (smoothed l0-norm) algorithm is a fast compressive-sensing-based DOA (direction-of-arrival) estimation algorithm that uses a single snapshot from the received signal. In the conventional SL0 algorithm, there are limitations in the resolution and the DOA estimation performance, since a single sample is used. If multiple snapshots are used, the conventional SL0 algorithm can improve performance in terms of the DOA estimation. In this paper, a covariance-fitting-based SL0 algorithm is proposed to further reduce the number of optimization variables when using multiple snapshots of the received signal. A cost function and a new null-space projection term of the sparse recovery for the proposed scheme are presented. In order to verify the performance of the proposed algorithm, we present the simulation results and the experimental results based on the measured data.

摘要

本文提出了一种用于无源相控阵系统的增强型平滑 l0 范数算法,该算法利用接收信号的协方差矩阵。SL0(平滑 l0 范数)算法是一种基于快速压缩感知的波达方向(DOA)估计算法,它使用接收信号的单个快照。在传统的 SL0 算法中,由于使用单个样本,在分辨率和 DOA 估计性能方面存在局限性。如果使用多个快照,传统的 SL0 算法可以在 DOA 估计方面提高性能。本文提出了一种基于协方差拟合的 SL0 算法,以在使用接收信号的多个快照时进一步减少优化变量的数量。给出了该方案的代价函数和稀疏恢复的新零空间投影项。为了验证所提算法的性能,我们给出了基于实测数据的仿真结果和实验结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b4c2/8272156/6d95cc46d938/sensors-21-04403-g001.jpg

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