Auto-Calibration and 2D-DOA Estimation in UCAs via an Integrated Wideband Dictionary

TL;DR

This paper introduces a novel auto-calibration method for 2D-DOA estimation in uniform circular arrays that uses an integrated wideband dictionary to improve accuracy and reduce computational complexity without prior knowledge of mutual coupling coefficients.

Contribution

The proposed method combines an integrated wideband dictionary with iterative refinement to enhance 2D-DOA and mutual coupling matrix estimation, reducing complexity and avoiding prior knowledge constraints.

Findings

Improved 2D-DOA estimation accuracy

Reduced computational complexity

Effective mutual coupling matrix estimation

Abstract

In this paper, we present a novel auto-calibration scheme for the joint estimation of the two-dimensional (2-D) direction-of-arrival (DOA) and the mutual coupling matrix (MCM) for a signal measured using uniform circular arrays. The method employs an integrated wideband dictionary to mitigate the detrimental effects of the discretization of the continuous parameter space over the considered azimuth and elevation angles. This leads to a reduction of the computational complexity and obtaining of more accurate DOA estimates. Given the more reliable DOA estimates, the method also allows for the estimation of more accurate mutual coupling coefficients. The method utilizes an integrated dictionary in order to iteratively refine the active parameter space, thereby reducing the required computational complexity without reducing the overall performance. The complexity is further reduced by employing only the dominant subspace of the measured signal. Furthermore, the proposed method does not require a constraint on the prior knowledge of the number of nonzero coupling coefficients nor suffer from ambiguity problems. Moreover, a simple formulation for 2-D non-numerical integration is presented. Simulation results show the effectiveness of the proposed method.