Cognitive FDA Radar Transmit Power Allocation for Target Tracking in Spectrally Dense Scenario

Abstract In this paper, we propose a cognitive radar paradigm based on frequency diverse array (FDA), which allows flexible spectrum control via element-wise transmit power allocation. As an emerging array technique, FDA differs from conventional phased array (PA) in that it imposes an additional frequency increment across the array elements. The use of frequency increment provides the FDA radar with the ability of flexible spectrum adjustment. We propose the cognitive FDA radar for target tracking in spectrally dense scenarios. Two optimization criteria, i.e., signal-to-interference-plus-noise ratio (SINR) maximization and Cramer-Rao bound (CRB) minimization, are employed to adaptively update the array weight vector for power allocation at each transmission. Numerical results show that the proposed cognitive FDA radar can adjust the signal spectrum to avoid the interfered frequencies for better output SINR. The resulting tracking errors of FDA radar with adaptive power allocation are lower than that for fixed power allocation. Moreover, the CRB criterion further improves the tracking performance.