Waveform optimization techniques for bi-static Cognitive Radars

We propose a convex optimization based waveform design technique for bi-static radars. The method exploits prior knowledge of the environment including clutter statistics to maximize accumulated target return signal power while keeping the disturbance power to unity at both the radar receivers. The problem was solved using an iterative optimization approach where the transmitted waveforms are determined using semi-definite programming while receiver filters are obtained using generalized eigenvalue decomposition. Simulation results demonstrate improved signal to disturbance ratio for both the radars.