Abstract:

The existing adaptive waveform and detection threshold algorithms for radar target tracking focus mostly on the one-dimensional target with the range and range rate as measurements. As it ignores the effect of the angle on target tracking, it is impossible to track and locate the target. A joint adaptive waveform and detection threshold algorithm for two-dimensional maneuvering target tracking in clutter background is proposed. First, the traditional theory based on the time delay-Doppler resolution cell is further extended to design a resolution cell with the “prism” structure, which includes the range-range rate and azimuth measurements. Then, an approximate joint expression for measurement error covariance, containing the waveform parameter and detection threshold, is given. Finally, inspired by the cognitive radar, the next waveform parameters and detection threshold are adaptively selected at the cost of minimizing the trace of filtering error covariance to improve the tracking performance of the system. Simulation results show that the performance of the waveform and detection threshold self-adaption algorithm is obviously superior to the fixed parameter algorithm.

Key words: cognitive radar, joint detection-tracking, resolution cell, waveform selection, adaptive detection threshold