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Two-Step Sparse Representation Based 2D DOA Estimation with Single Moving Acoustic Vector Sensor

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Abstract

This paper investigates the two dimensional direction of arrival (2D DOA) estimation problem of multiple sources with one single moving acoustic vector sensor (AVS). We first use one single moving AVS to construct a synthetic nested AVS array, which is later shown that is equivalent to the physical nested AVS array. Then the vectorization and row extraction operations are performed to obtain the observation vector that behaves like signals received by a virtual uniform AVS array. Finally, the 2D DOA estimation is obtained via a two-step sparse representation (SR) method, which transforms the 2D grid search to a computationally efficient 1D grid search. The Cramer-Rao bound comparison between the synthetic and physical nested AVS arrays shows that these two arrays are equivalent for DOA estimation. Based on the property of the nested arrays and the full utilization of the array aperture via SR, the proposed method can achieve better estimation performance than spatial smoothing methods with nested AVS arrays and methods with uniform AVS arrays. Simulations validate the effectiveness of the proposed synthetic array method.

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Acknowledgements

This work is supported by China NSF Grants (61371169, 61601167, 61601504), Jiangsu NSF (BK20161489), the open research fund of State Key Laboratory of Millimeter Waves, Southeast University (No. K201826), and the Fundamental Research Funds for the Central Universities (NO.NE2017103).

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China

    Zhan Shi, Xiaofei Zhang & Wang Zheng

  2. State Key Laboratory of Millimeter Waves, Southeast University, Nanjing, 210096, China

    Xiaofei Zhang

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  1. Zhan Shi
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  2. Xiaofei Zhang
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  3. Wang Zheng
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Correspondence to Zhan Shi.

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Shi, Z., Zhang, X. & Zheng, W. Two-Step Sparse Representation Based 2D DOA Estimation with Single Moving Acoustic Vector Sensor. Wireless Pers Commun 111, 2561–2575 (2020). https://doi.org/10.1007/s11277-019-07003-8

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