An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising

Abstract

Co-prime arrays can estimate the directions of arrival (DOAs) of scriptO(MN) sources with scriptO(M+N) sensors, and are convenient to analyze due to their closed-form expression for the locations of virtual lags. However, the number of degrees of freedom is limited due to the existence of holes in difference coarrays if subspace-based algorithms such as the spatial smoothing multiple signal classification (MUSIC) algorithm are utilized. To address this issue, techniques such as positive definite Toeplitz completion and array interpolation have been proposed in the literature. Another factor that compromises the accuracy of DOA estimation is the limitation of the number of snapshots. Coarray-based processing is particularly sensitive to the discrepancy between the sample covariance matrix and the ideal covariance matrix due to the finite number of snapshots. In this paper, coarray interpolation based on matrix completion (MC) followed by a denoising operation is proposed to detect more sources with a higher accuracy. The effectiveness of the proposed method is based on the capability of MC to fill in holes in the virtual sensors and that of MC denoising operation to reduce the perturbation in the sample covariance matrix. The results of numerical simulations verify the superiority of the proposed approach.

Doa Estimation Using Triply Primed Arrays Based on Fourth-Order Statistics

“…In this work, TPA (3,4,5) and TPA (3,5,7) are constructed and compared with CPA (3,5). TPA (3,4,5) and CPA (3,5) are composed of 10 physical sensors, while TPA(3, 5, 7) is composed of 13 physical sensors.…”

“…By applying MUSIC algorithm, with the covariance matrix processed by a spatial smoothing technique, the DOF reaches O(MN ). In [7], a MUSIC-based method with array interpolation and matrix denoising was proposed to fill the holes in a virtual coarray and reduce the estimation error of covariance matrix due to finite snapshots. In [8], an ESPRIT-based method was proposed to estimate the DOAs without resorting to spatial smoothing, peak search or a predefined grid.…”

DOA-Based Localization Method with Multiple Screening K-Means Clustering for Multiple Sources

“…e existing two-step positioning method consists of two processes: parameter estimation and position calculation. e commonly used parameters mainly include time of arrival (TOA), time delay of arrival (TDOA), direction of arrival (DOA), and Doppler shift parameters [1][2][3]. e DOA parameter estimation is mainly based on array signal processing methods.…”

Direct Position Determination of Coherently Distributed Sources based on Compressed Sensing with a Moving Nested Array

“…P ositioning technology is one of the important contents of signal processing in recent years， which is widely applied in earthquake monitoring, smart city, industrial 4.0 and so on [1,2,3,4]. The current positioning technologies are mainly divided into two-step positioning methods and direct position determinations(DPD) methods.…”