Adaptive transmit beamspace design for cognitive FDA radar tracking

In this study, the authors propose an energy‐efficient adaptive transmit beamspace design for cognitive frequency diverse array (FDA) radar to efficiently detect and track the target in a cognitive way, particularly, for the case when the target is lost in one scan. Additionally, an algorithm is presented for a selection of the illumination range‐angle sector to recover a lost target. Moreover, an algorithm is proposed to discriminate the target from interferers, while an FDA beampattern time‐variance that is normally ignored in the literature is also considered. Finally, the transmit beamspace is adaptively updated to illuminate the predicted range‐angle‐based area of interest in each cognitive scanning cycle. The proposed design generates a single maximum beam pattern by using a set of non‐uniform frequency offsets along an FDA. Numerical results show that the proposed method achieves improved target detection and tracking performance as compared to the standard frequency diverse and phased‐array radars due to its increased output signal‐to‐interference‐plus‐noise ratio, while improved energy efficiency is achieved due to an adaptive range‐angle sector selection algorithm.