A Gridless Fourth-order Cumulant-Based DOA Estimation Method under Unknown Colored Noise

TL;DR

This paper introduces a gridless DOA estimation method using fourth-order cumulants that effectively suppresses colored noise and extends to sparse linear arrays, validated by numerical simulations.

Contribution

It presents a novel gridless DOA estimation approach based on fourth-order cumulants and atomic norm minimization, improving noise robustness and array flexibility.

Findings

Effective noise suppression demonstrated in simulations

Method extends to sparse linear arrays

Achieves stable and accurate DOA estimation

Abstract

To reduce the adverse impacts of the unknown colored noise on the performance degradation of the direction-of-arrival (DOA) estimation, we propose a new gridless DOA estimation method based on fourth-order cumulant (FOC)in this letter. We first introduce the non-redundancy single measurement vector (SMV) through FOC, which is capable of suppressing the Gaussian colored noise. Next, we analyze the distribution of the estimation error and design an estimation error tolerance scheme for it. We then combine the atomic norm minimization of the non-redundancy SMV with the above constraint scheme. This combination poses the stability of the sparsest solution. Finally, the DOA estimation is retrieved through rotational invariance techniques. Moreover, this method extends the gridless DOA estimation to the sparse linear array. Numerical simulations validate the effectiveness of the proposed method.