Title
Generalized Covariance-Based Esprit-Like Solution To Direction Of Arrival Estimation For Strictly Non-Circular Signals Under Alpha-Stable Distributed Noise
Abstract
Direction of arrival (DOA) estimation with high resolution and low computational complexity has been one essential research topic. Meanwhile, many solutions have been proposed to handle parameter estimation problems for strictly non-circular (NC) signals. However, second-order statistics-based solutions usually degrade under fractional lower-order Alpha-stable distributed noise. To solve this problem, three concepts are first defined, and then related properties are proved, including a specific generalized covariance (GC), the non-circularity based on GC, and the extended GC matrix. Based on these concepts and theorems, a novel ESPRIT-like method is derived especially for strictly non-circular sources and termed NC-GC-ESPRIT. Monte-Carlo simulations under four different experimental conditions are executed, involving eleven state-of-the-art DOA approaches as comparison candidates. Thus, the superior performance of the proposed solution is validated through the comparison with these candidate algorithms. (C) 2021 Elsevier Inc. All rights reserved.
Year
DOI
Venue
2021
10.1016/j.dsp.2021.103214
DIGITAL SIGNAL PROCESSING
Keywords
DocType
Volume
Alpha-stable distribution, Direction of arrival, ESPRIT, Generalized covariance, Non-circular signals
Journal
118
ISSN
Citations 
PageRank 
1051-2004
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Shengyang Luan164.85
Jiayuan Li211.04
Yinrui Gao331.43
Jinfeng Zhang400.34
Tianshuang Qiu531343.84