The Real-Valued Sparse Direction of Arrival (DOA) Estimation Based on the Khatri-Rao Product
AbstractThere is a problem that complex operation which leads to a heavy calculation burden is required when the direction of arrival (DOA) of a sparse signal is estimated by using the array covariance matrix. The solution of the multiple measurement vectors (MMV) model is difficult. In this paper, a real-valued sparse DOA estimation algorithm based on the Khatri-Rao (KR) product called the L1-RVSKR is proposed. The proposed algorithm is based on the sparse representation of the array covariance matrix. The array covariance matrix is transformed to a real-valued matrix via a unitary transformation so that a real-valued sparse model is achieved. The real-valued sparse model is vectorized for transforming to a single measurement vector (SMV) model, and a new virtual overcomplete dictionary is constructed according to the KR product’s property. Finally, the sparse DOA estimation is solved by utilizing the idea of a sparse representation of array covariance vectors (SRACV). The simulation results demonstrate the superior performance and the low computational complexity of the proposed algorithm. View Full-Text
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Chen, T.; Wu, H.; Zhao, Z. The Real-Valued Sparse Direction of Arrival (DOA) Estimation Based on the Khatri-Rao Product. Sensors 2016, 16, 693.
Chen T, Wu H, Zhao Z. The Real-Valued Sparse Direction of Arrival (DOA) Estimation Based on the Khatri-Rao Product. Sensors. 2016; 16(5):693.Chicago/Turabian Style
Chen, Tao; Wu, Huanxin; Zhao, Zhongkai. 2016. "The Real-Valued Sparse Direction of Arrival (DOA) Estimation Based on the Khatri-Rao Product." Sensors 16, no. 5: 693.
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