Spectrally Constrained MIMO Radar Waveform Design Based on Mutual Information

Abstract

We address the waveform design problem for multiple-input multiple-output (MIMO) radar in spectrally crowded environments. We exploit the mutual information between the target reflections and the target responses as the design metric. To tackle the associated nonconvex optimization problem, we propose an algorithm based on first-order Taylor series approximation as well as minorization-maximization (MM) based algorithms to design the spectrally constrained waveforms. Interestingly, for some scenarios, we can synthesize the globally optimal (spectrally constrained) waveforms with the maximum mutual information. We also show that, through intelligent waveform design, MIMO radar can coexist more efficiently with other communication systems occupying the same spectrum, while suffering from insignificant mutual information losses.