Abstract
In this article, the direction-of-arrival (DOA) estimation problem of wideband signal sources is studied. We pass the incident signals through a bank of narrowband filters to split the array outputs into several narrowband components. Then, a novel slice-sparse representation model of the joint narrowband array covariance data is proposed in the frequency domain to enforce joint sparsity in the concatenated covariance matrix of all frequencies. Based on the greed matching pursuit algorithm, a multiple measurement slices orthogonal matching pursuit algorithm is proposed to exploit the joint frequency processing in the case of wideband scenarios. The DOA estimation is achieved by joint processing of the array covariance data at different frequency bins. The estimated performance is compared with the representative DOA estimation methods. Simulation experiments are conducted to validate the effectiveness of the proposed method.
Highlights
Due to the increase use of wideband signals in the fields of wireless communication system and radar, the problem of direction of arrival (DOA) estimation of wideband signals has been of considerable interest to the array signal processing in recent years
The results indicate that MUSIC, coherent signal-subspace method (CSSM), wideband covariance matrix sparse representation (W-CMSR) all cannot express angular distribution correctly and pseudo-peaks exist in the spectrum of the three while the measurement slices (MMS)-OMP algorithm can gain two correct peaks at 10◦ and 30◦
5 Conclusion In this article, we are engaged in the DOA estimation of wideband signal sources
Summary
Due to the increase use of wideband signals in the fields of wireless communication system and radar, the problem of direction of arrival (DOA) estimation of wideband signals has been of considerable interest to the array signal processing in recent years. To work in the frequency domain, we propose a slice-SR model of the joint array covariance data that are stacked as a tensor matrix. Based on the greedy matching pursuit algorithm [11,12], we propose a multiple measurement slices (MMS) orthogonal matching pursuit (MMS-OMP) algorithm This algorithm processes the narrowband covariance data jointly to obtain the spatial-frequency spectrum. (2) The proposed method is based on the greedy pursuit algorithms so that, it is a low-complexity and high resolution estimator for the wideband signal sources. The wideband DOA estimation method proposed in section can be derived from SR of the array output covariance vectors in R (fj)
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