[关键词]
[摘要]
由于海面目标个数多、密集、进出雷达视野随机变化性强,而且杂波密度高,目标速度模糊等原因导致机载雷达跟踪性能下降。文中提出了基于随机集理论框架下的海面目标跟踪算法。首先,设计了基于LDL分解的高斯混合势概率假设密度(GM-CPHD)滤波算法用来降低算法的计算量;接着,提出了融入径向速度的目标跟踪算法来提高海面目标跟踪性能;最后,设计了仿真示例。仿真结果表明:该算法在提高跟踪性能的同时可以减少20??的计算量。
[Key word]
[Abstract]
The characteristics of random variant, high number, heavy clutter and heavy target density make difficult for airborne radar tracking in the scenario of air-to-sea targets tracking. A tracking algorithm is proposed in order to solve this problem. Gaussian mixture cardinality probability hypothesis density (GM-CPHD) filter algorithm based on LDL decomposition which called LDL-GMCPHD filter is presented to reduce complexity firstly , and a tracking algorithm with Doppler radius is designed to improve performance secondly. Numerical example is also given in the manuscript lastly and the simulation results show that the proposed tracking algorithm can track sea surface moving multi-target with superior performance while 20?? degraded computation.
[中图分类号]
TN959. 7
[基金项目]