基于对称熵的预警雷达时间资源管理算法

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

    • 摘要: 由于机载预警雷达天线扫描周期长,跟踪目标容量大而密集,若逐一回访目标,将拉长扫描周期使多数目标外推时间拉长到不可接受的程度,因此被跟踪目标的波束回访需被动态实时管控。为此,文中提出了基于Beta-Gamma对称信息熵的相控阵预警雷达波束回访时间资源管理算法。首先,设计了相控阵预警雷达搜索和跟踪模型;其次,设计了目标优先级计算方法用于选择参与波束回访的目标集合;接着,根据雷达快速目标调度算法计算波束回访间隔;最后,根据目标航迹的Beta-Gamma对称信息熵对存在调度竞争的目标进行排序决策,选出急需调度的目标进行雷达波束回访。数字仿真结果证实了所提算法可以实时准确地响应波束回访资源占比的需求。

       

      Abstract: 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.

       

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