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Direction finding based on iterative adaptive approach utilizing weighted \(\ell _2\)-norm penalty for acoustic vector sensor array

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Abstract

It is well known that the iterative adaptive approach (IAA) is an effective direction-of-arrival (DOA) estimation method for large aperture array, high signal-to-noise ratio (SNR) and large source separation. However, its derivation is obtained by minimizing a weighted least square cost function without considering the sparsity of solution, it cannot work properly in low SNR, small aperture array and small source separation scenarios. In this paper, to address this problem, the weighted \(\ell _2\)-norm based IAA, namely as WIAA, is proposed to provide accurate DOA utilizing acoustic vector sensor array (AVSA). First, to improve the sparsity of solution for IAA, the auxiliary cost function with respect to the signal, which is penalized by the \(\ell _{2}\)-norm with a user parameter, is reconstructed based on the spatial sparsity of signal. Then, to obtain an analytical solution, the Majorization-minimization algorithm is used to turn the penalty term with a user parameter into a weighted \(\ell _2\)-norm one. Finally, the sparse solution is quantified by the Frobenius norm properties. Several simulation and experimental results verify the superiority of the WIAA method compared to some other existing algorithms.

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Acknowledgements

This research was supported by National Natural Science Foundation of China under Grant 61531015 and 62101176, the National Key Research and Development Program of China under Grant 2016XFC1400203, The Science, Technology and Innovation Commission of Shenzhen Municipality under Grant JCYJ20180306170932431, the Research Project of Guizhou University for Talent Introduction (no. [2020]61), and the Cultivation Project of Guizhou University (no. [2019]56).

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Authors and Affiliations

  1. School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo, 454000, China

    Weidong Wang & Hui Li

  2. College of Computer Science and Technology, State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, China

    Weijie Tan

  3. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, 710072, China

    Wentao Shi & Qunfei Zhang

  4. Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China

    Wentao Shi

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  1. Weidong Wang
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Correspondence to Wentao Shi.

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Wang, W., Tan, W., Shi, W. et al. Direction finding based on iterative adaptive approach utilizing weighted \(\ell _2\)-norm penalty for acoustic vector sensor array. Multidim Syst Sign Process 33, 247–261 (2022). https://doi.org/10.1007/s11045-021-00797-6

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