학술논문
3rd–order cumulants-based DOA estimation in the presence of colored Gaussian noise
Document Type
Conference
Author
Source
OCEANS 2022, Hampton Roads OCEANS Hampton Roads, 2022. :1-4 Oct, 2022
Subject
Language
Abstract
Most of the existing direction of arrival estimation methods are based on either autocorrelations or the even-order cumulants of the data, and assume that the noise is to be spatially white with known autocorrelations matrix. For direction of arrival estimation in the presence of spatially colored Gaussian noise, this paper defines a particular rectangular 3 rd -order cumulants matrix of the received data, and hence proposes a Rectangular MUltiple SIgnal Classification algorithm. The proposed method is more capable to suppress the spatially correlated as well as uncorrelated Gaussian noise than its equivalent autocorrelations-based method, and hence have improved direction of arrival estimation performance, especially with spatially-colored Gaussian noise. Numerical results proves the efficacy of the proposed method compared to its equivalent autocorrelations-based method.