NoncovANM: Gridless DOA Estimation for LPDF System

TL;DR

This paper introduces a low-cost, high-resolution DOA estimation method using an IRS-aided LPDF system with a novel nonconvex atomic norm minimization approach, reducing complexity and hardware costs while improving accuracy.

Contribution

The paper proposes a nonconvex ANM method with gradient threshold iteration for efficient DOA estimation in IRS-aided LPDF systems, addressing complexity and hardware cost issues.

Findings

Outperforms existing methods in DOA estimation accuracy.

Reduces computational complexity compared to traditional ANM.

Provides theoretical convergence analysis and CRLB derivation.

Abstract

Direction of arrival (DOA) estimation is an important research in the area of array signal processing, and has been studied for decades. High resolution DOA estimation requires large array aperture, which leads to the increase of hardware cost. Besides, high accuracy DOA estimation methods usually have high computational complexity. In this paper, the problem of decreasing the hardware cost and algorithm complexity is addressed. First, considering the ability of flexible controlling the electromagnetic waves and low-cost, an intelligent reconfigurable surface (IRS)-aided low-cost passive direction finding (LPDF) system is developed, where only one fully functional receiving channel is adopted. Then, the sparsity of targets direction in the spatial domain is exploited by formulating an atomic norm minimization (ANM) problem to estimate the DOA. Traditionally, solving ANM problem is complex and cannot be realized efficiently. Hence, a novel nonconvex-based ANM (NC-ANM) method is proposed by gradient threshold iteration, where a perturbation is introduced to avoid falling into saddle points. The theoretical analysis for the convergence of the NC-ANM method is also given. Moreover, the corresponding Cram\'er-Rao lower bound (CRLB) in the LPDF system is derived, and taken as the referred bound of the DOA estimation. Simulation results show that the proposed method outperforms the compared methods in the DOA estimation with lower computational complexity in the LPDF system.