Abstract-A new robust beamforming algorithm for multiple-input and multiple-output (MIMO) radar is proposed in the presence of unknown mismatches phenomenon of the desired signal steering vector. Considering that the transmitted waveforms of MIMO radar are orthogonal to each other, after matched filtering MIMO radar can be thought equivalent to multiple single input and multiple output (multi-SIMO) radars. So we decomposed the full-dimensional beamforming of MIMO radar into multiple dimension-reduced beamforming for equivalent multi-SIMO radars. This kind of equivalent has benefits of reducing the number of whole sampling data and the dimensions of sampling data that each equivalent SIMO radar needs to process. Otherwise, we used particle swarm optimization (PSO) algorithm to modify the mismatch of each desired signal steering vector, and the robustness has been greatly improved because the use of PSO. Numerical experiments with the desired signal steering vector mismatches are provided to demonstrate the effectiveness of the proposed dimension-reduced robust adaptive beamforming algorithm.

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A new adaptive pulse compression (APC) method has been proposed in this paper in order to restrain the mutual interference of the orthogonal transmitted waveforms. Based on the minimum power distortionless response (MPDR) this method is combined by the generalized sidelobe canceller (GSC) structure and the multistage wiener filter (MWF), which not only does not calculate the covariance matrix of signal samples and its inverse matrix, but also reduces the computational complexity compared with the APC method based on recursive minimum mean-square error (RMMSE) and generalized sidelobe canceller (GSC). Simulation results validate the new technique is more effective than the conventional matched filter (MF), and shows a similar behavior with the RMMSE and GSC algorithms.