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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。
Aiming at the lack of priori information of trajectory association and systematic error distribution, an error registration algorithm of radar system is proposed by using the PPLI reporting function of cooperative participation of data link system. The algorithm maps the radar-PPLI trajectory pairs into a set of parameter domain points and defines the trust function in the parameter domain. It is proved that under certain assumptions, the trust function converges to the mean with the systematic error point State distribution probability density function, preliminary estimation of radar system error by searching peak of trust function. Based on this, the global optimal relation between radar track and PPLI track is solved and the radar system error is estimated accurately. Monte Carlo simulation shows that the performance of the algorithm is close to Cramér-Rao lower bound.