Wideband Direction of Arrival Estimation with Sparse Linear Arrays

Conference paper (2020)

Authors

F. Wang Signal Processing Systems - EEMCS , University of Electronic Science and Technology of China
Zhi Tian George Mason University
Jun Fang University of Electronic Science and Technology of China
G.J.T. Leus Signal Processing Systems - EEMCS
Research Group
Signal Processing Systems (EEMCS) (TU Delft)
Copyright: © 2020 F. Wang, Zhi Tian, Jun Fang, G.J.T. Leus
DOI: https://doi.org/10.1109/ICASSP40776.2020.9053681
Sparse linear array (SLA) Jacobi-Anger approximation Atomic norm minimization (ANM) Wideband direction of arrival (DoA) estimation
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Published Date

2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

This paper concerns wideband direction of arrival (DoA) estimation with sparse linear arrays (SLAs). We rely on the assumption that the power spectrum of the wideband sources is the same up to a scaling factor, which could in theory allow us to resolve not only more sources than the number of antennas but also more sources than the number of degrees of freedom (DoF) of the difference co-array of the SLA. We resort to the Jacobi-Anger approximation to transform the coarray response matrices of all frequency bins into a single virtual uniform linear array (ULA) response matrix. Based on the obtained model, two super-resolution DoA estimation approaches based on atomic norm minimization (ANM) are proposed, one with and one without prior knowledge of the power spectrum. Simulation results show that our proposed methods outperform the state of the art and are indeed capable of resolving more sources than the number of DoF of the difference co-array.