摘要
针对满足一些状态约束的线性系统,通常的卡尔曼滤波未能有效利用状态约束信息,从而限制了导航定位解算性能的问题,该文将线性系统的状态约束条件融入卡尔曼滤波中,充分利用状态约束信息,对比分析了准确测量法、估计投影法、系统投影法和滑动时域估计法4种状态约束下的卡尔曼滤波方法,以提高卡尔曼滤波的导航状态估计精度。以陆地车辆导航定位的状态估计为对象,对比分析了非约束卡尔曼滤波和带有状态约束的卡尔曼滤波的状态估计精度,结果表明,状态约束卡尔曼滤波可以明显提高导航定位精度。
Aiming at the problem that usual Kalman filtering can not effectively utilize the state constraint information,consequently the performance of navigation and positioning is restricted for linear systems that satisfy some state constraints.This paper provided four ways to incorporate state constraint in Kalman filtering,they are perfect measurement,estimate projection,system projection and moving horizon estimation.The state estimation of land vehicle navigation and positioning was taken as the research object,the state estimation accuracy of unconstrained Kalman filter and the Kalman filter with state constraints was compared and analyzed.The results showed that the Kalman filter with state constraints can significantly improve the navigation accuracy.
作者
周晓敏
刘海颖
蒋鑫
夏露
ZHOU Xiaomin;LIU Haiying;JIANG Xin;XIA Lu(The First Geodetic Surveying Brigade of NASG, Xi＇ an 710054, China;College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;The First Institute of Aero-photogrammetry and Remote Sensing, NASG, Xi＇an 710054, China)
出处
《测绘科学》
CSCD
北大核心
2018年第4期109-113,121,共6页
Science of Surveying and Mapping
基金
国家重点研发计划项目(2016YFB0501401)
航空科学基金项目(20150852013)
江苏省自然科学基金项目(BK20161490)
中央高校基本科研业务专项(2015097)
关键词
卡尔曼滤波
状态约束
导航定位
精度分析
Kalman filtering
state constraints
navigation and positioning
accuracy analysis
作者简介
周晓敏（1972-），女，陕西蒲城人，高级工程师，硕士，主要研究方向为摄影测量与遥感的技术管理和应用。E—mail：410426390@qq．com
