Abstract

This paper studies the optimization of waveform covariance matrix (WCM) for airborne multiple-input-multiple-output (MIMO) radar systems in the presence of clutter and jamming. The goal is to enhance the target detection performance by suppressing the clutter and jamming based on space time adaptive processing (STAP). We employ the signal-to-interference-plus-noise ratio (SINR) as the figure of merit. Assuming a known target steering vector, we recast the WCM design problem into a convex optimization problem. Through a max-min approach, we also make the designed WCM robust to the target steering vector, i.e., we develop a method to design WCM that maximizes the worst-case SINR associated with an uncertainty set. We explicitly derive the target steering vector corresponding to the worst-case SINR and solve the robust design of WCM via convex optimization. Finally, we provide several numerical examples to demonstrate the superiority of the proposed algorithms over the existing methods.

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