摘要
为了得到适用于射程修正引信的弹丸落点预测方法,研究了基于扩展卡尔曼滤波的雷达跟踪弹道辨识算法和基于数理统计理论的弹丸落点预测精度分析方法.最后,采用蒙特卡洛模拟方法对弹道辨识进行了仿真研究,仿真结果表明扩展卡尔曼滤波是辨识雷达跟踪弹道的有效方法,当雷达采样时间约在15.0 s以上时,落点预测距离相对误差小于0.42%,满足射程修正引信的性能指标要求.
A trajectory identification method for range correcting fuze to accurately predict the impact points of projectiles from radar tracking trajectory data is presented. The identification algorithms are formulated within extended Kalman filtering framework, and the accuracy of impact point prediction is evaluated based on the symbolic statistics theory. The algorithms are demonstrated through Monte Carlo simulation. The simulation statistic results show that the extended Kalman filtering is an effective method of performing radar tracking trajectory identification, and when the radar measurement time is above 15. 0 s, the accuracy of the impact point prediction is better than 0. 42Y0, which satisfy the requirements of range correcting fuze.
出处
《西安工业大学学报》
CAS
2011年第4期392-396,共5页
Journal of Xi’an Technological University
关键词
精度分析
射程修正引信
弹道辨识
雷达跟踪
accuracy analysis
range correcting fuze
trajectory identification
radar tracking
