A Novel ULA-Difference-Coarray-Based DOA Estimation Method for General Coherent Signals

Zhang Chen,Hao Wu,Yongxiang Liu,Wang Zheng

doi:10.1155/2020/1548016

Zhang Chen, Hao Wu + Show 2 more

Open Access

https://doi.org/10.1155/2020/1548016

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Abstract

In this article, a difference-coarray-based direction of arrival (DOA) method is introduced, which utilizes the uniform linear array (ULA) in a novel fashion to address the problem of DOA estimation for coherent signals. Inspired by the coarray-based estimators employed in cases of sparse arrays, we convert the sample covariance matrix of the observed signals into the difference coarray domain and process the signals using a spatial smoothing technique. The proposed method exhibits good accuracy and robustness in both the uncorrelated and coherent cases. Numerical simulations verify that the ULA difference coarray- (UDC-) based method can achieve good DOA estimation accuracy even when the SNR is very low. In addition, the UDC-based method is insensitive to the number of snapshots. Under extremely challenging conditions, the proposed UDC-ES-DOA method is preferred because of its outstanding robustness, while the UDC-MUSIC method is suitable for most moderate cases of lower complexity. Due to its demonstrated advantages, the proposed method is a promising and competitive solution for practical DOA estimation, especially for low-SNR or snapshot-limited applications.

Highlights

Antenna-array-based direction of arrival (DOA) estimation algorithms have been widely used in radar, navigation, measurement, and control systems
Inspired by the coarray-based estimators employed in cases of sparse arrays, we convert the sample covariance matrix of the signals observed by a uniform linear array (ULA) into the difference coarray domain and pretreat the signals using an spatial smoothing (SS) method
Inspired by the coarray-based estimators employed in cases of sparse arrays, we attempt to convert the sample covariance matrix of the signals observed by the ULA into the difference coarray domain

Summary

Introduction

Antenna-array-based direction of arrival (DOA) estimation algorithms have been widely used in radar, navigation, measurement, and control systems. In some practical scenarios, such as indoor environments, the signals may be highly correlated (coherent) due to multipath propagation In this case, the signal covariance matrix is no longer nonsingular, and as a result, the performance of the abovementioned subspace-based DOA algorithms will deteriorate dramatically. The signal covariance matrix is no longer nonsingular, and as a result, the performance of the abovementioned subspace-based DOA algorithms will deteriorate dramatically To address this problem, the most common method is to pretreat the observed signals using a spatial smoothing (SS). There are some methods that are developed based on the spatial differencing technique to address the DOA estimation problem of the mixed uncorrelated and coherent sources in multipath environment [14,15,16]. Diag{} is a diagonal matrix operator, and vec () denotes an operator that returns the vectorization result of a matrix. (_)T, (_)H, and (_)∗ stand for transpose, conjugate transpose, and complex conjugate, respectively. ⊙ depicts the KR product, and ⊗ denotes the Kronecker product

Preliminaries

Proposed UDC-DOA Method

Numerical Examples

Findings

Conclusions