Limited by the number of antenna elements, conventional array radars usually have insufficient ability of signal-dependent interference suppression in harsh environments, even though transmit and receive beamformers are jointly designed. This article deploys an active reconfigurable intelligent surface (RIS) to assist the receive array, which provides numerous extra degrees-of-freedom to suppress interferences and to enhance the beamforming gain of target echo simultaneously since the active RIS has the capability of adjusting and amplifying incident signals. Aiming to maximize the output signal-to-interference-plus-noise ratio (SINR), we jointly design the phase-only or power-limited transmit beamformer, receive beamformer, and active RIS reflection coefficients. We devise an alternating optimization-based algorithm to handle the resultant nonconvex-constrained fractional programming problem. Specifically, the phase-only transmit beamformer is determined by the Riemannian gradient descent (RGD)-based method while the power-limited one is given as a closed-form optimal solution, and the active RIS reflection coefficients are updated by the concave-convex procedure (CCCP)-based method. Moreover, we derive the convergence condition of the proposed algorithm based on the properties of RGD and CCCP. Numerical results reveal that the proposed active RIS-aided array radar significantly outperforms the passive RIS-aided and RIS-free ones in terms of output SINR.
更多
查看译文
关键词
Radar,Signal to noise ratio,Reconfigurable intelligent surfaces,Array signal processing,Passive radar,Reflection,Radar detection,Interference suppression,Wireless communication,MIMO radar,Reconfigurable intelligent surface,beamforming,interference suppression,riemannian manifold optimization,concave-convex procedure