Optimised radar waveform design based on the relative entropy constraint

Abstract

A new strategy to optimise the waveform of multiple-input multiple-output (MIMO) radar under the relative entropy constraint and signal-to-noise ratio (SNR) constraint is presented. The Kullback–Leibler divergence (KLD) is exploited between the two probability density functions of binary hypothesis testing as the design metric. A particular analysis of detection performance is made here to illuminate the balance between the false alarm and missing alarm probabilities. The results of the simulation demonstrate that the waveform design process constrained by relative entropy outperforms the process employing an explicit SNR constraint when the SNR is relatively low (i.e., within the interval [−2 dB, 0.5 dB]). The enhanced performance is attributable to the capability of the proposed optimisation process to focus the energy of the transmission waveform onto components where the eigenvalues of the target signal are large and the eigenvalues of the noise are small.