Joint Transmit and Receive Beamforming for Cognitive FDA-MIMO Radar With Moving Target

Abstract

Cognitive radars can possess intelligent active sensing ability and adapt complex variable environment. Inspired by this technology, a cognitive frequency diverse array multiple-input multiple-output (FDA-MIMO) radar is proposed to apply for surveillance and detect the moving target timely. FDA-MIMO radar is a novel array structure which employs the small frequency offset across the transmit waveform to produce the range-angle dependent beampattern. The range-angle dependent beampatterns have ability to suppress the jammers when they are located at the same angle of the target. To obtain the maximum signal-to-interference-plus-noise-ratio (SINR) and suppress the jammers effectively, we consider the transmit and receive beamforming filters design and proposed an iterating optimization algorithm to obtain optimal beamforming filters. For the moving target, the Extended Kalman filter (EKF) method is utilized to update the position of the target and the new position information is applied for the filters design to obtain optimal performance of SINR timely. In addition, expressions for the detection probability and SINR are deduced for the FDA-MIMO radar target detection. Finally, numerical results show that the proposed cognitive FDA-MIMO radar can effectively suppress the jammers and detect the moving target.