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This paper considers the joint design of transmit waveforms and receive filters for airborne multiple-input-multiple-output (MIMO) radar systems. The aim is to maximize the output signal-to-interference-plus-noise ratio (SINR) such that we can achieve enhanced detection performance for a slow-moving target that might be obscured by clutter and jamming. We devise a cyclic algorithm to tackle the non-convex joint design problem. Considering practical implementation issues, we extend the algorithm to deal with constrained designs (i.e., the design of waveforms under a constant-envelope constraint and a similarity constraint, respectively). The convergence of all the devised algorithms is guaranteed. We provide several numerical examples to demonstrate the effectiveness of the proposed algorithms. [ABSTRACT FROM PUBLISHER]

Previous work on multiple-input multiple-output (MIMO) radar waveform design in colored noise based on minimizing minimum mean-square error (MMSE) and normalized mean-square error (NMSE) only considered the optimization of the singular value of the waveform matrix, while the optimization of singular vectors, which forms a basis of singular value optimization, was not stressed enough. In this correspondence, we revisit the waveform design problem for MIMO radar in colored noise based on MMSE and NMSE respectively. Further results for the optimal solutions under both criteria are derived. We prove the optimality of “matching” with the target and colored noise for the singular vectors of the transmitted waveform. Moreover, to obtain minimum MMSE/NMSE, the pairing of the eigenvectors of the target and noise should be carefully designed, where the optimal pairing of the eigenvectors based on MMSE is fixed while the optimal pairing based on NMSE changes according to the transmitted power, the strength of the target, and noise. [ABSTRACT FROM PUBLISHER]