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Aiming at the problems of poor accuracy, low angular resolution, and low degree of freedom in traditional bistatic nested multiple input multiple output (MIMO) radar for target parameter estimation, a method based on the use of virtual redundant array elements is proposed. The reconstructed Toeplitz matrix algorithm is a method of parameter estimation for the direction of departure (DOD) and direction of arrival (DOA) of the target. Firstly, the two nested sub-arrays are arranged with the zero point as the center to form the receiving array and the transmitting array of the bistatic MIMO radar. The virtual receiving signal processed by the array has a large number of redundant virtual array elements. Second, the covariance values corresponding to the redundant virtual array elements are averaged to replace the original values to form a new virtual received signal, and then two selection matrices are used to construct spatial smoothing sub-arrays in the virtual receiving array and the virtual transmitting array. The method reconstructs the Toeplitz matrix to reconstruct the virtual received signal. Finally, the conventional subspace algorithm is used to estimate the space spectrum of the equivalent virtual signal to realize the mutual matching of DOD and DOA. The proposed algorithm compares better with other algorithms in terms of estimation performance and degree of freedom performance. [ABSTRACT FROM AUTHOR]

Based on low-rank matrix reconstruction theory, this paper proposes a joint DOD and DOA estimation method for coherent targets with bistatic coprime array MIMO radar. Unlike the conventional vectorization, the proposed method processed the coprime array with virtual sensor interpolation, which obtained a uniform linear array to generate the covariance matrix. Then, we reconstructed the Toeplitz matrix and established a matrix optimization recovery model according to the kernel norm minimization theory. Finally, the reduced dimension multiple signal classification algorithm was applied to estimate the angle of the coherent targets, with which the automatic pairing of DOD and DOA could be realized. With the same number of physical sensors, the proposed method expanded the array aperture effectively, so that the degree of freedom and angular resolution could be improved significantly for coherent signals. However, the effectiveness of the method was largely limited by the signal-to-noise ratio. The superiority and effectiveness of the method were proved using simulation experiments. [ABSTRACT FROM AUTHOR]

This paper proposes a method to address the problem of the joint direction of departure (DOD) and direction of arrival (DOA) estimation with augmented coprime array (CPA) bistatic multiple input multiple output (MIMO) radar using interpolating sensors. At first, we deduce the regular pattern of hole positions in the virtual array and interpolate a small number of sensors to augmented CPA to form a partially contiguous virtual array. Then, we use the diversity smoothing algorithm to reconstruct the Toeplitz matrix to obtain a spatial smoothing matrix. Finally, we combine the RD-MUSIC algorithm with the spatial smoothing matrix to estimate the spatial spectrum and achieve automatic matching of DODs and DOAs for the targets. Simulation results clearly illustrate the superiority of the method. [ABSTRACT FROM AUTHOR]