Parameter Estimation for Reconfigurable Holographic Surfaces enabled Radars

Abstract

Parameter estimation is a fundamental task for radar sensing, which is traditionally realized by phased array based radars. However, due to the power-consuming hardware components such as phase shifters, the size of the phased array is constrained given the available power for the radar system, thus leading to a limited estimation precision of phased array based radars. To address this issue, we propose the holographic radar system enabled by the reconfigurable holographic surface (RHS), which is a novel type of metamaterial antenna with simple hardware and low power consumption. Since the desired beams of the RHS are generated by controlling the amplitudes of the signals radiated by the RHS elements, traditional beamforming schemes developed for phased arrays do not fit any more. Therefore, we develop a new beamforming scheme for the RHS-based parameter estimation. In more detail, we derive and analyze the Cramér-Rao bound (CRB) to evaluate the lower bound of estimation error. A CRB minimization problem is then formulated to optimize the estimation precision, and an RHS amplitude optimization algorithm is designed to solve the problem. Simulation results show that for the same power consumption, the estimation precision of the proposed holographic radar can outperform that of the phased array counterpart.