YAN Xiao-long1, CHEN Guo-guang1, BAI Dun-zhuo2
（1. College of Mechatronic Engineering, North University of China, Taiyuan 030051, China; 2. Yuxi Industries Group Co.,Ltd., Nanyang 473000, China）
Abstract： In order to measure the parameters of flight rocket by using radar, rocket impact point was estimated accurately for rocket trajectory correction. The Kalman filter with adaptive filter gain matrix was adopted. According to the particle trajectory model, the adaptive Kalman filter trajectory model was constructed for removing and filtering the outliers of the parameters during a section of flight detected by three-dimensional data radar and the rocket impact point was extrapolated. The results of numerical simulation show that the outliers and noise in trajectory measurement signal can be removed effectively by using the adaptive Kalman filter and the filter variance can converge in a short period of time. Based on the relation of filtering time and impact point estimation error, choosing the filtering time of 8-10 s can get the minimum estimation error of impact point.
Key words： rocket; adaptive Kalman filter; outliers; impact point estimation
CLD number： TJ415Document code： A
Article ID： 1674-8042（2015）03-0212-06 doi： 10.3969/j.issn.1674-8042.2015.03.002
References
［1］ WANG Zhi-xian. Optimal state estimation and identification system. Xi’an: Northwestern Polytechnical University Press, 2004.
［2］ SHI Jing-guang, XU Ming-you, WANG Zhong-yuan, et al. Application of Kalman filtering in calculation of trajectory falling point of trajectory correction projectiles. Journal of Ballistics, 2008, 20(3): 41-44.
［3］ GAO Ning, ZHOU Yue-qing, YANG ye, et al. Adaptive Kalman filter algorithm with fault-tolerant improvement. Journal of Chinese Inertial Technology, 2003, 11(3): 25-28.
［4］ ZHANG Yuan, CHEN Yong, WU Hao. Study of ballistic missile impact point prediction. Missiles and Space Vehicles, 2014, (3): 5-10.
［5］ LI Guang-jun, LI Zhong, CUI Ji-ren. Research on new Kalman filter restraining outliers. Computer Applications and Software, 2013, 30(1): 136-138.
［6］ ZHAO Han-dong, LI Qiang, JIAO Jun-hu, et al. The study on improvment of firing accuracy of rocket projectile using impact point predication guidance law. Journal of Projectiles, Rockets, Missiles and Guidance, 2009, 29(3): 169-172.
［7］ YANG Shu-xing, ZHANG Cheng, ZHU Bo-li. Unsophisticated control method for long-range rockets. Transactions of Beijing Institute o f Technology, 2004, 24(6): 486-491.
［8］ XU Ming-you. Advanced exterior ballistics. Beijing: High Education Press, 2003.
［9］ HAN Zi-peng. Exterior ballistics of projectiles and rockets. Beijing: Beijing Institute of Technology Press, 2008.
自适应卡尔曼滤波器在火箭弹落点估计中的应用
闫小龙1， 陈国光1， 白敦卓2
（1. 中北大学 机电工程学院， 山西 太原 030051； 2. 豫西工业集团有限公司， 河南 南阳 473000）
摘要:利用雷达对火箭弹一段飞行过程中的参数进行量测， 对火箭弹落点进行了准确估计， 实现了火箭弹的轨迹修正。采用具有自适应调节滤波增益矩阵的卡尔曼滤波器， 结合质点弹道模型， 建立了自适应卡尔曼滤波弹道模型， 完成了对三坐标雷达探测的一段火箭弹飞行参数的野值处理与滤波， 并对火箭弹落点进行外推。 数值仿真结果表明， 经自适应调节的卡尔曼滤波器滤波后， 弹道量测信号中的野值与噪声被有效去除， 且滤波方差可以在短时间内收敛。 根据滤波时间与落点估计误差的关系， 采用滤波时间为8-10 s方案， 可得到最佳的落点估计。
关键词:火箭弹； 自适应卡尔曼滤波器； 野值； 落点估计
引用格式：YAN Xiao-long, CHEN Guo-guang, BAI Dun-zhuo. Application of adaptive Kalman filter in rocket impact point estimation. Journal of Measurement Science and Instrumentation, 2015, 6(3)： 212-217.［doi： 10.3969／j.issn.1674-8042.2015.03.002］
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