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In this paper, we focus on the problem of direction-of-arrival (DOA) estimation for a colocated multiple-input multiple-output radar with imperfect waveforms, and a parallel factor (PARAFAC)-based algorithm is proposed. First, the spatial cross-correlation technique is adopted to eliminate the spatially colored noise caused by the nonorthogonal waveforms. To utilize the inherent tensor structure of the array data, the covariance matrix is rearranged into a fourth-order PARAFAC decomposition model. Thereafter, a quadrilinear decomposition algorithm is developed, which obtain the direction matrices via alternating least squares strategy. Finally, the DOAs are achieved through solving a least squares fitting problem. The proposed scheme does not require the prior knowledge of the waveform correlation matrix, and it is computationally more efficient than the state-of-the-art matrix completion (MC) approach. Furthermore, the proposed method may offer more accurate DOA estimation performance than the MC approach. The numerical experiments are provided to show the improvement of our algorithm.

A PARAFAC Decomposition Algorithm for DOA Estimation in Colocated MIMO Radar With Imperfect Waveforms