Time Resource Management Algorithm of Early Warning Radar Based on Symmetric Entropy

Due to the long scanning period of the airborne early warning radar antenna and the large and dense tracking capacity of targets, revisiting each target will excessively prolong the scanning period, making the extrapolation time for most targets unacceptably long. Therefore, a dynamic real-time beam management is required for tracked targets. A time resource management algorithm for the beam revisit of a phased array early warning radar based on Beta-Gamma symmetric information entropy is proposed to address this problem in this paper. Firstly, searching and tracking model is designed for phased array early warning radar. Secondly, a target priority calculation method to select the set of targets participating in beam revisit is addressed. Then, the beam revisit interval is calculated according to a fast target scheduling algorithm. Finally, a ranking decision for the targets with scheduling competition is made according to the Beta-Gamma symmetric information entropy of the target tracks, thereby selecting the most urgently needed targets for radar beam revisit. The numerical simulation results confirm that the proposed algorithm can accurately and instantly respond to the demand for beam revisit resource allocation.