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Rank Minimization-Based Toeplitz Reconstruction for DoA Estimation Using Coprime Array by Shengheng Liu; Zihuan Mao; Yimin D. Zhang; Yongming Huang is a Engineering article available to read on EtoBox.

What is Rank Minimization-Based Toeplitz Reconstruction for DoA Estimation Using Coprime Array about?

In this paper, we address the problem of direction finding using coprime array, which is one of the most preferred sparse array configurations. Motivated by the fact that nonuniform element spacing hinders full utilization of the underlying information in the receive signals, we propose a directionof-arrival (DoA) estimation algorithm based on low-rank reconstruction of the Toeplitz covariance matrix. The atomicnorm representation of the measurements from the interpolated virtual array is considered, and the equivalent dual-variable rank minimization problem is formulated and solved using a cyclic optimization approach. The recovered covariance matrix enables the application of conventional subspace-based spectral estimation algorithms, such as MUSIC, to achieve enhanced DoA estimation performance. The estimation performance of the proposed approach, in terms of the degrees-of-freedom and spatial resolution, is examined. We also show the superiority of the proposed method over the competitive approaches in the root-mean-square error sense.

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Author

Shengheng Liu; Zihuan Mao; Yimin D. Zhang; Yongming Huang

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Published

2021

Language

EN

Field

Engineering (Physical Sciences)