基于改进无迹卡尔曼滤波的弹道射程修正算法研究

doi:10.3969/j.issn.1000-1093.2018.09.005

兵工学报 ›› 2018, Vol. 39 ›› Issue (9): 1701-1710.doi: 10.3969/j.issn.1000-1093.2018.09.005

基于改进无迹卡尔曼滤波的弹道射程修正算法研究

雷晓云，张志安，杜忠华

（南京理工大学机械工程学院，江苏南京 210094）

收稿日期:2017-10-20 修回日期:2017-10-20 上线日期:2018-10-25
通讯作者: 张志安（1979—），男，副教授，硕士生导师 E-mail:zzayoyo@163.com
作者简介:雷晓云（1990—），女，博士研究生。E-mail：leixiaoyunray@126.com
基金资助:
国家自然科学基金项目（11372142）

Ballistic Range Correction Algorithm Based on an Improved Unscented Kalman Filter

LEI Xiao-yun, ZHANG Zhi-an, DU Zhong-hua

(School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China)

Received:2017-10-20 Revised:2017-10-20 Online:2018-10-25

摘要/Abstract

摘要： 以全球定位系统（GPS）作为弹载测量系统的弹道射程修正弹，存在GPS动态数据易受测量噪声与系统噪声污染或在高过载环境中发生定位丢失、数据异常等问题。为了降低弹道数据测量误差，并减小对射程修正时刻预测的误差，提出了基于牛顿插值法的改进无迹卡尔曼滤波(UKF)算法，以重新估计具有粗大误差的测量数据，从而降低异常测量值和定位失锁情况对滤波效果的影响，提高UKF算法对测量数据误差的敏感程度。仿真与试验结果表明：改进的UKF算法作为预处理过程融合至射程修正算法中，当系统离散化步长与GPS数据更新周期相等时，可最大化地预处理算法效果；改进后的修正算法可有效地降低GPS数据造成的修正误差；预处理算法中数据样本容量的选择与修正时刻以及GPS更新周期相关，不受算法效果约束。

关键词: 弹道射程修正, 预处理, 无迹卡尔曼滤波, 射程修正, 全球定位系统

Abstract: For the ballistic range correction projectiles utilizing GPS as the projectile-borne detection system, the received dynamic data is susceptible to contamination from measurement noise and system noise, and data loss and exception happen in the high-overload environment. An improved unscented Kalman filter (UKF) based on Newton interpolation method is proposed to reduce the measurement error, thereby decreasing the predicted error during range correction. Data sets with abnormal errors are distinguished and reestimated. The improved UKF algorithm is used to reduce the influence of abnormal measurements and data loss on filtering effect, and more sensitive to measurement error. The improved unscented Kalman filter is designed to be adopted in an ballistic range correction algorithm. The simulated and test results indicate that the preprocessing effect could be maximized if the step size of system discretization is equal to the GPS update interval; the improved correction algorithm is able to reduce the correction errors induced by GPS data. The sample size of GPS data in preprocessing is related to the correction moment and GPS update interval, and it is not restricted by the algorithm effect.Key

Key words: ballisticrangecorrection, preprocessing, unscentedKalmanfilter, rangecorrection, globalpositioningsystem

中图分类号:

TJ413⁺.6

雷晓云，张志安，杜忠华. 基于改进无迹卡尔曼滤波的弹道射程修正算法研究[J]. 兵工学报, 2018, 39(9): 1701-1710.

LEI Xiao-yun, ZHANG Zhi-an, DU Zhong-hua. Ballistic Range Correction Algorithm Based on an Improved Unscented Kalman Filter[J]. Acta Armamentarii, 2018, 39(9): 1701-1710.

参考文献

［1］杨小会, 霍鹏飞, 王超. 基于卡尔曼滤波的GPS弹道测量误差消除方法[J]. 探测与控制学报, 2012,34(4):30-33.
YANG Xiao-hui, HUO Peng-fei. WANG Chao. GPS trajectory errors elimination based on Kalman filtering[J]. Journal of Detection and Control, 2012,34(4)：30-33.(in Chinese)
[2］ Moraes R V D, Silva A A D, Kuga H K. Simple orbit determination using GPS based on a least-squares algorithm employing sequential givens rotations[J]. Mathematical Problems in Engineering, 2007(1):57-76.
[3］ Fu W X, Rizos C. The applications of wavelets to GPS signal processing[C]∥Proceedings of the 10th International Technical Meeting of the Satellite Division of the Institute of Navigation. Kansas City, MO, US: Institute of Navigation, 1996: 697-703.
[4］ Lee S C, Liu C Y. Trajectory estimation of reentry vehicles by use of on-line input estimator [J]. Journal of Guidance, Control, and Dynamics, 1999, 22(6): 808-815.
[5］ Maley J M. Efficient attitude estimation for a spin-stabilized projectile[J]. Journal of Guidance, Control, and Dynamics, 2015, 39(2): 339-350.
[6］ Nisar S, Ullah I. Non-linear filtering techniques for high precision GPS applications[C]∥Proceedings of International Conference on Communication, Computing and Digital Systems. Islamabad, Pakistan:IEEE, 2017:276-280.
[7］ Gaebler J, Sun S D, Carpenter R. Comparison of sigma- point and extended Kalman filters on a realistic orbit determination scenario[J]. The Journal of the Astronautical Sciences, 2012, 59(1/2): 301-307.
[8］ Yang C, Shi W, Chen W. Comparison of unscented and extended Kalman filters with application in vehicle navigation[J]. The Journal of Navigation, 2017, 70(2): 411-431.
[9］曾广裕, 申强, 李东光, 等. 基于扩展卡尔曼滤波的全球导航卫星系统矢量跟踪建模与仿真[J]. 兵工学报, 2015, 36(3): 530-538.
ZENG Guang-yu, SHEN Qiang, LI Dong-guang, et al. Modeling and simulation on GNSS vector tracking loop based on extended Kalman filtering[J]. Acta Armamentarii,2015, 36(3): 530-538.(in Chinese)

[10］杨帆, 芮筱亭, 王国平. 提高弹道导弹命中精度方法研究[J]. 南京理工大学学报, 2007, 31(1):10-16.
YANG Fan, RUI Xiao-ting, WANG Guo-ping, Method to improve firing accuracy of ballistic missiles[J].Journal of Nanjing University of Science and Technology, 2007, 31(1): 10-16.(in Chinese)
[11］韩子鹏，赵子华，刘世平,等. 弹箭外弹道学[M]. 北京：北京理工大学出版社, 2008:23-83.
HAN Zi-peng， ZHAO Zi-hua, LIU Shi-ping, et al. Exterior ballistics of projectiles and rockets[M]. Beijing: Beijing Institute of Technology Press，2008:23-83.(in Chinese)
[12］谢钢. GPS原理与接收机设计[M].北京：电子工业出版社, 2009: 78-79.
XIE Gang. Principles of GPS and receiver design [M]. Beijing: Publishing House of Electronics Industry, 2009: 78-79.(in Chinese)
[13］ Julier S J, Uhlmann J K, Durrant-Whyte H F. A new approach for filtering nonlinear systems[C]∥American Control Conference. Anchorage, AK, US：IEEE, 2002:1628-1632.
[14］黄小平, 王岩. 卡尔曼滤波原理及其应用[M].北京: 电子工业出版社, 2015: 36-37.
HUANG Xiao-ping, WANG Yan. Principle and application of Kalman filter[M].Beijing: Publishing House of Electronics Industry, 2015:36-37.(in Chinese)

第39卷
第9期2018 年9月兵工学报ACTA
ARMAMENTARIIVol.39No.9Sep.2018

[1]	王振峰，李飞，王新宇，杨建森，秦也辰. 基于交互式多模型无迹卡尔曼滤波的悬架系统状态估计[J]. 兵工学报, 2021, 42(2): 242-253.
[2]	张征, 刘春光, 马晓军, 张运银. 一种基于数据融合的全轮驱动车辆质心侧偏角估计方法[J]. 兵工学报, 2020, 41(5): 842-849.
[3]	洪升，李洁，董延焘，赵志欣，王玉皞. 多输入多输出天波超视距雷达多模杂波抑制的改进最小方差无失真响应算法研究[J]. 兵工学报, 2020, 41(5): 911-923.
[4]	张梦得, 李开龙, 胡柏青, 吕旭. 辅助信息源短时失效下的捷联惯性基组合导航算法[J]. 兵工学报, 2020, 41(10): 2008-2015.
[5]	张成举，王聪，曹伟，王金强. 基于无迹卡尔曼滤波的超空泡航行体最优控制研究[J]. 兵工学报, 2019, 40(6): 1235-1243.
[6]	马艳，刘小东. 状态自适应无迹卡尔曼滤波算法及其在水下机动目标跟踪中的应用[J]. 兵工学报, 2019, 40(2): 361-368.
[7]	李群生，赵剡，王进达. 一种适用于高动态强干扰环境的视觉辅助微机械捷联惯性导航系统/全球定位系统超紧组合导航系统[J]. 兵工学报, 2019, 40(11): 2241-2249.
[8]	谢恺，秦鹏程. 基于七维状态向量反向无迹卡尔曼滤波的弹道外推算法[J]. 兵工学报, 2018, 39(10): 1945-1950.
[9]	郑恩明，陈新华，宋春楠. 基于全相位预处理的低旁瓣波束形成方法[J]. 兵工学报, 2018, 39(10): 1971-1978.
[10]	丁传俊，张相炎，刘宁. 基于自适应无迹卡尔曼滤波算法的多股螺旋弹簧动态响应模型参数辨识和分析[J]. 兵工学报, 2018, 39(1): 28-37.
[11]	王啸, 韩太林, 张永立, 刘轩, 王义君, 宫玉琳. 多通道瞬态信号自适应变频算法[J]. 兵工学报, 2017, 38(6): 1161-1167.
[12]	向颉，茅永兴，郭才发. 船载雷达测速数据的船速修正新方法[J]. 兵工学报, 2017, 38(11): 2268-2273.
[13]	孔筱芳，陈钱，顾国华，钱惟贤，任侃，王佳节. 基于全球定位系统的相机标定方法研究[J]. 兵工学报, 2016, 37(12): 2301-2307.
[14]	朱明强，侯建军，刘颖，李旭，田洪娟. 适于无线传感网络目标追踪的一种改进无迹粒子滤波时延差估计算法[J]. 兵工学报, 2015, 36(7): 1266-1272.
[15]	潘加亮，熊智，王丽娜，郁丰，赵慧，林爱军. 一种简化的发射系下SINS/GPS/CNS组合导航系统无迹卡尔曼滤波算法[J]. 兵工学报, 2015, 36(3): 484-491.

基于改进无迹卡尔曼滤波的弹道射程修正算法研究

Ballistic Range Correction Algorithm Based on an Improved Unscented Kalman Filter

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价