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One-Bit Gridless DOA Estimation with Multiple Measurements Exploiting Accelerated Proximal Gradient Algorithm

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Abstract

With low hardware cost and power consumption, direction-of-arrival (DOA) estimation exploiting one-bit quantized array data has become an attractive topic. In this paper, the gridless compressed sensing (CS) with multiple measurement vectors for one-bit DOA estimation is investigated. First, the one-bit quantized signal model is established. Then an atomic norm minimization scheme is proposed based on the output of one-bit quantizer, in which the objective function is reformulated as a semidefinite programming problem combined with a one-sided \(l_1\)-norm constraint, representing the sign inconsistency between the quantized and unquantized measurements. To efficiently solve such a problem and reduce its computational complexity, an accelerated proximal gradient-based algorithm is developed. The proposed approach outperforms the one-bit MUSIC in a small number of measurements, and avoids the grid-mismatch issue of several existing one-bit CS methods. Numerical experiments are conducted to validate the superiorities of the proposed one-bit DOA estimation approach in accuracy and running time.

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Acknowledgements

This document is the results of the research funded by the National Natural Science Foundation of China under Grants 61371158 and 61771217, and the Natural Science Foundation of Jilin Province (CN) under Grant 20180101329JC.

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  1. College of Communication Engineering, Jilin University, Changchun, 130012, China

    Wen-Gen Tang, Hong Jiang & Qi Zhang

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  1. Wen-Gen Tang
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  2. Hong Jiang
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  3. Qi Zhang
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Correspondence to Hong Jiang.

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Tang, WG., Jiang, H. & Zhang, Q. One-Bit Gridless DOA Estimation with Multiple Measurements Exploiting Accelerated Proximal Gradient Algorithm. Circuits Syst Signal Process 41, 1100–1114 (2022). https://doi.org/10.1007/s00034-021-01829-z

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