Robust Beamforming Design for Monostatic ISAC Systems Based on Minimum Mean-Square Error Estimation

In this paper, we investigate the robust waveform design problem for integrated sensing and communications (ISAC) in the presence of imperfect communcation channel state information (CSI). Specifically, the estimation error obtained through the minimum mean squared error (MMSE) criterion is used to represent sensing performance. Subsequently, under the premise of minimizing the estimation error, constraints on signal-to-interference-plus-noise ratio (SINR) outage probability and power budget are introduced. The non-convex optimization problem is then addressed using the semidefinite relaxation (SDR) and sphere bounding method. Simulation results demonstrate a enhancement in both sensing and communication performance with the proposed robust waveform design, validating the effectiveness and robustness of the proposed approach.