In this paper, an aperture expanding direction finding algorithm using L-shaped non-uniform sparse array is proposed. Firstly, the virtual array is expanded by vectorization, de-redundancy and sorting of received data covariance matrix. Secondly, the full rank matrix is got by smoothing the virtual array data, and the signal subspace is obtained by matrix block processing and matrix operation. Finally, the elevation angle and azimuth angle are acquired by using the rotation invariant relation. The algorithm does not need to decompose the covariance matrix of the data, nor does it need to search the two-dimensional spectral peaks. It can greatly reduce the computational complexity when there are many array elements and large number of snapshots. The simulation results show that the sparse array arrangement can enlarge the array aperture, improve the parameter resolution and the accuracy of DOA estimation, and verify the effectiveness of the proposed algorithm.
The interelement spacing of a coprime array breaks through the half-wavelength limitation, so that a larger array aperture can be obtained with a fixed number of array elements. In this paper, the symmetry of the noncircular signal is used to virtually expand the L-shaped array into an orthogonal cross array. Furthermore, the virtual received signal of the augmented array is obtained by the second-order statistic of the received data. Decoupling and dimension reduction of elevation and azimuth are realized by a z-axis subarray and y-axis subarray. Finally, the sparse reconstruction of the signal is realized by the minimum absolute convergence and selection operator method. This method can enlarge the aperture and freedom of array and has higher accuracy and resolution of DOA estimation. It has the advantages of automatic parameter pairing without additional pairing operation and is effective for coherent and incoherent signals. The final numerical simulation results prove the effectiveness of the method in this paper.
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