Space- Time-Range Adaptive Processing for MIMO Radar Imaging

Multiple-input multiple-output (MIMO) radar has drawn considerable attention due to its superior performance over phased array radar. The performance is achieved through waveform diversity. In terms of MIMO radar space-time adaptive processing (STAP), it is often assumed that the received signals has already been separated by a bank of matched filters (MFs) or the covariance matrix of the waveforms is an identity matrix. We find that when the non-complete orthogonality of the waveforms is taken into consideration, MIMO radar STAP suffers performance degradation. Besides, inspired by the definition of waveform diversity, a space-time-range adaptive processing (STRAP) scheme is proposed based on the framework of adaptive pulse compression (APC) and the criterion of minimum variance distortionless response (MVDR) to overcome the influence of non-completely orthogonal waveforms by taking into account the interference of nearby range cells to estimate the covariance matrix. The proposed algorithms are assessed via simulation experiments in two scenarios in comparison with sequential processing and the results show the effectiveness of STRAP.