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2017•IET Radar Sonar & NavigationRequires access

Efficient sparse representation method for wideband DOA estimation using focusing operation

Yonghong Zhao, Linrang Zhang, Yabin Gu, Yumei Guo, Juan Zhang

Open publisher page 13 citations

Abstract

The computational complexity of wideband sparse representation (SR) greatly restricts the application of SR‐based wideband direction‐of‐arrival (DOA) estimation in practical system. Here, an efficient method for wideband direction finding based on SR is proposed. This method combines the focusing operation with weighted subspace fitting (WSF) to not only decrease the computational complexity but also improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularisation parameter is given by the asymptotic distribution of the WSF cost function. Simulations are provided to show the efficiency and performance of the proposed method.

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What this paper is about

The computational complexity of wideband sparse representation (SR) greatly restricts the application of SR‐based wideband direction‐of‐arrival (DOA) estimation in practical system. Here, an efficient method for wideband direction finding based on SR is proposed. This method combines the focusing operation with weighted subspace fitting (WSF) to not only decrease the computational complexity but also improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularisation parameter is given by the asymptotic distribution of the WSF cost function. Simulations are provided to show the efficiency and performance of the proposed method.

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Available abstract

The computational complexity of wideband sparse representation (SR) greatly restricts the application of SR‐based wideband direction‐of‐arrival (DOA) estimation in practical system. Here, an efficient method for wideband direction finding based on SR is proposed. This method combines the focusing operation with weighted subspace fitting (WSF) to not only decrease the computational complexity but also improve the performance of DOA estimation. Exploiting the result of the focusing operation, the covariance matrix at the focusing frequency can be obtained and used as the data for sparse recovery to get wideband DOA estimates. The WSF is employed to reduce the sensitivity to the noise and the regularisation parameter is given by the asymptotic distribution of the WSF cost function. Simulations are provided to show the efficiency and performance of the proposed method.

Key concepts: Wideband, Sparse approximation, Representation (politics), Computer science, Direction of arrival, Algorithm, Subspace topology, Covariance matrix

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