Cyclostationarity-based DOA estimation algorithms for coherent signals in impulsive noise environments

Yang Liu,Yinghui Zhang,Jing Gao,Tianshuang Qiu,Qiong Wu

doi:10.1186/s13638-019-1410-8

Abstract

Estimating direction of arrival (DOA) is important in a variety of practical applications. Conventional cyclostationarity-based coherent DOA estimation algorithms are not robust to non-Gaussian α-stable impulsive noise. Additionally, fractional lower-order statistics (FLOS)-based algorithms are tolerant to impulsive noise; however, they experience performance degradation for coherent signals and interference. To overcome these drawbacks, two types of fractional lower-order cyclostationarity-based subspace DOA estimation methods are proposed for coherent signals in the presence of interference and α-stable impulsive noise. The new proposed algorithms exploit the fractional lower-order cyclostationarity properties of the signals and are immune to the impulsive noise and interference. Moreover, they can provide more accurate DOA estimates of coherent signals than conventional cyclostationarity-based and FLOS-based methods. The simulation results illustrate the robustness and effectiveness of the proposed methods for coherent signals based on a comparison with traditional methods. The new algorithms can be used in the presence of a wide range of interference, Gaussian noise, and α-stable distribution impulsive noise environments.

Highlights

The direction of arrival (DOA) is the base problem in array signal processing and is the core of many civilian and military applications, such as communication regulation enforcement, search-and-rescue operations, and military reconnaissance [1,2,3]
If received signals can be divided into the signal of interest (SOI) and interference based on their cyclostationary characteristics, the signals of interest can be selected and the noise and interfering signals can be removed by utilizing cyclostationarity [17]
We address the issue of the DOA estimation of cyclostationary coherent signals in impulsive noise environments

Summary

Introduction

The direction of arrival (DOA) is the base problem in array signal processing and is the core of many civilian and military applications, such as communication regulation enforcement, search-and-rescue operations, and military reconnaissance [1,2,3]. There are many advantages of DOA estimation using cyclostationary characteristics compared to conventional methods [18, 19] These advantages include selective direction finding, interference and noise suppression, and breakthrough-limited multi-signal processing. We are interested in developing DOA algorithms that are robust to interference, Gaussian noise, and non-Gaussian α-stable distribution noise and that account for the coherent signals in real-world environments. Two novel types of robust fractional lower-order cyclostationarity-based signal-selective subspace DOA estimation algorithms for coherent signals are developed. Compared with conventional cyclic subspace DOA estimation algorithms, the proposed methods are immune to the interference and Gaussian noise, but can account for impulsive noise and coherent signals. The proposed DOA estimation algorithms have three notable advantages over traditional methods: (1) in the presence of interfering signals, the proposed methods exhibit signal selectivity and performance improvements over the FLOS-based MUSIC and ESPRIT algorithms; (2) in impulsive environments, the proposed methods are more robust to impulsive noise than the cyclic MUSIC and cyclic ESPRIT algorithms; and (3) the proposed methods are effective for cyclostationary coherent signals in impulsive noise and interference environments, while conventional coherent cyclic methods are limited to DOA estimation from Gaussian noise, and FLOS-based coherent methods exhibit degradation in the presence of interference

Methods

Influence of coherent signals

Conclusions