基于数据链的雷达误差配准算法

Radar System Error Registration Algorithm Based on Data Link

针对没有航迹关联和系统误差分布先验信息的情况,利用数据链系统合作目标的精确参与平台定位与识别(PPLI)报告功能,提出了一种雷达系统误差配准算法。算法将雷达与PPLI航迹对映射为参数域点集,定义了参数域上的信任函数,证明了在一定假设下信任函数随公共航迹数量增加依概率收敛于以系统误差点为均值的正态分布概率密度函数,通过搜索信任函数峰值初步估计雷达系统误差。在此基础上求解雷达航迹与PPLI航迹全局最优关联关系并精确估计雷达系统误差。通过蒙特卡洛仿真验证了算法性能接近Cramér-Rao下界。

Utilizing the Precise Participant Location and Identification （PPLI） reporting function of cooperative targets in data link system, a radar registration algorithm was proposed without a priori information of track-to-track association and the radar system error distribution. A point set was obtained by mapping radar and PPLI track pairs to parameter domain. A credit function was defined on parameter domain. Under some assumptions, it was proved that, as the number of common tracks increased, the credit function was convergent in probability to the probability density function of the normal distribution which was centered at the system error point. The radar system error could be estimated preliminarily by searching the credit function＇s peak point, and the track-to- track association problem among bias- compensated radar tracks and PPLI tracks was formulized as a linear program problem to resolve the global optimal track assignment. The radar system error was precisely estimated according the result of track association. The availability of the proposed algorithm was validated by Monte Carlo simulations, which shows that the performance is close to the Cram6r-Rao lower bound.