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This letter considers the direction of arrival (DOA) estimation of non-circular (NC) source using a large uniform linear array with a single snapshot. First, by utilizing the waveform characteristics of the NC signal, the proposed algorithm can enlarge the virtual array aperture that is twice the length of the physical array, and resultantly enhance DOA estimation accuracy. Moreover, by multiplying a correction matrix, the proposed algorithm can offset the NC phase error, thereby obtain further improved DOA estimation performance. Furthermore, the advocated algorithm can reduce the computation complexity by using the Newton-Raphson method instead of the traditional grid-search method. Finally, the numerical simulation results are provided to demonstrate the effectiveness and superiority of the proposed algorithm.

Compared with nested array, coprime array can significantly alleviate the mutual coupling between array sensors due to the sparser array structure. However, plenty of holes in its difference co-array extremely reduce the achievable number of uniform degrees of freedom(uDOFs). In this letter, a coprime array with prime integer 3(CAP-3) is proposed, in contrast to several well-known nested arrays, which can offer comparable number of uDOFs, and alleviate mutual coupling simultaneously. Specifically, the CAP-3 consists of three appropriately placed subarrays, and it can eradicate most of the holes in difference co-array except two at both ends. Hence a large number of uDOFs can be obtained. Furthermore, CAP-3 possesses robustness against heavy level of mutual coupling due to the reduced number of sensor pairs with small inter-element spacing. Simulations reveal the advantage of the CAP-3 in uDOF, mutual coupling robustness, and direction of arrival estimation accuracy.

In this letter, two-dimensional (2D) direction of arrival (DOA) estimation using one-dimensional (1D) nested array motion is studied, and an improved Discrete Fourier transform (DFT) algorithm is proposed. Exploiting nested array to move vertically along its axis enables 2D DOA estimation with large-scale and hole-free difference co-array. DFT algorithm has lower complexity than multiple signal classifications(MUSIC) method, but traditional DFT algorithm still requires multiple extra searches to ensure estimation accuracy. We use DFT to obtain the initial angle estimations, and then compensate the estimation offsets via total least squares (TLS) constructed from Taylor expansion approximation. Compared with the traditional DFT search method, the proposed method has lower complexity and better performance. Multiple simulations are conducted to verify the effectiveness of our approach.