30th Signal Processing and Communications Applications Conference, SIU 2022, Safranbolu, Turkey, 15 - 18 May 2022
© 2022 IEEE.In this study, a cognitive radar system that optimizes radar waveform parameters to increase the accuracy of radar tracking systems and balance time resource management is discussed. In the study, a cost function for the optimization of waveform parameters is proposed with the help of unscented Kalman filter (UKF) and interacting multiple models (IMM) methods. Thus, the tracking performance of targets with various movement types has been increased and the time resource has been used more efficiently. The performance of the proposed system is examined under a target tracking scenario that includes various maneuvers. In the analyzed scenario, the effect of the proposed cost function on the system performance was evaluated through track continuity, track estimation accuracy and time resource consumption. When the results obtained with the help of computer-aided simulations are examined, it is observed that the track update interval and the duration of stay on the target are updated adaptively according to the position and maneuver status of the target, and thus the time resource is consumed more efficiently.