A novel direction-of-arrival (DOA) estimator is proposed for the mixed uncorrelated and correlated wideband sources in the multipath environment. Firstly, the novel signal model is established using the aligned envelope technique. Next, the estimator can be divided into two parts. Theoretical analyses show that the correlated components cannot form peaks and only the DOA of uncorrelated signals can be acquired in the first part. Then, the correlated components are extracted from the corresponding covariance matrix and handled in the second part. Using the concept of linear search, the computational complexity of the algorithm is significantly reduced. Simulation results show the direction of uncorrelated and correlated wideband signals can be processed and distinguished effectively in the proposed method. Compared with previous DOA estimators for correlated wideband sources, the estimation accuracy has been improved.

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Researchers have recently shown an increased interest in estimating the direction‐of‐arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace‐based methods. An off‐grid sparse recovery‐based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal‐to‐noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer–Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.

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