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Sparse continuous-field and super-resolution method for direction-of-arrival estimation

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Abstract

In the application of direction-of-arrival (DOA) estimation based on sensor array, bearing-discretization has been a major technique for the sparsity-based methods in the past decade. However, discretization leads to the modeling error of sparse representation, which usually deteriorates the accuracy of DOA estimation. In this paper, a sparse continuous-field and super-resolution method (SCSM) is proposed to overcome the discretization issue. SCSM estimates DOA in the continuous bearing-space by solving a minimization problem, which combines the measurement covariance fitting criterion with the source-sparsity constraint characterized by minimizing an atomic norm. This minimization problem has a unique solution. After obtained the solution uniquely, Prony’s method is utilized to estimate the DOA of sources. Therefore, SCSM has the capability to acquire a sparse and accurate estimation of DOA. In addition, it has some other advantages, including excellent super-resolution capability, no requirement of source number, applicability to arbitrary number of snapshots. Numerical results demonstrate the superior performance of the presented method.

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Authors and Affiliations

  1. College of Science, National University of Defense Technology, Changsha, 410073, China

    Bo Lin & Jubo Zhu

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  1. Bo Lin
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  2. Jubo Zhu
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Correspondence to Bo Lin.

Additional information

This research was supported by the National Natural Science Foundation of China under Grants (Nos. 61601479, 61405251 and 61471369) and Research Programme of National University of Defense Technology (No. JC14-02-03).

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Lin, B., Zhu, J. Sparse continuous-field and super-resolution method for direction-of-arrival estimation. Multidim Syst Sign Process 28, 329–340 (2017). https://doi.org/10.1007/s11045-016-0451-y

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  • DOI: https://doi.org/10.1007/s11045-016-0451-y

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