Array covariance matrix-based atomic norm minimization for off-grid coherent direction-of-arrival estimation
Yu Zhang, Gong Zhang, Xinhai Wang
Abstract
A two-stage method for off-grid coherent direction-of-arrival (DOA) estimation using atomic norm minimization based on the covariance matrix is proposed in this paper. In the first stage, by vectorizing the covariance matrix, a new off-grid model matched as a linear combination of two dimensional harmonic is presented, where the proposed denoising covariance matrix-based atomic norm minimization (DCMANM) is applied for the vectorized covariance matrix denoising. Then the simplified dual polynomial method (SDPM) is used for DOA estimation. Unlike most of existing methods, the proposed method requires knowing neither the number of signals nor the statistics of noise. Numerical simulations demonstrate the outperformance of the proposed method in both the angle resolution and DOA estimation precision compared to the state-of-the-art approaches.
BibTeX
@inproceedings{icassp2017_arraycovariancem,
title = {Array covariance matrix-based atomic norm minimization for off-grid coherent direction-of-arrival estimation},
author = {Yu Zhang and Gong Zhang and Xinhai Wang},
booktitle = {ICASSP 2017},
year = {2017}
}