摘要
为满足高性能惯性/全球卫星导航系统(GPS)组合导航的要求,进一步提高卡尔曼滤波算法在组合导航定位中的解算精度,考虑利用逆向数据处理和加权平滑的融合算法,提出一种正逆向融合的卡尔曼滤波算法应用于惯性/GPS的松组合导航中。分析了正逆向融合的卡尔曼滤波算法的解算方法,并与普通正向卡尔曼滤波算法做出比较。实验部分采用车载传感器采集的实测数据,通过对两种方法解算结果的误差分析,表明了正逆向融合的滤波算法在定位精度方面优于传统正向滤波算法。
In order to meet the requirements of high performance of INS/GPS integrated navigation system and further improve the calculation accuracy of Kalman filtering algorithm in the integrated navigation position,a reverse data processing and smoothed smoothing fusion algorithm are proposed in this paper.A forward and reverse fusion Kalman filtering algorithm is applied to the loose combination of INS/GPS integrated navigation system.The calculation method of the forward and reverse fusion Kalman filtering algorithm is analyzed and is compared with the normal forward Kalman filter algorithm.In the experiment section,the data collected by the vehicle sensors are used.Through analyzing the errors of the two kinds of algorithms,it is showed that the forward and reverse fusion filtering algorithm has better performance than that of the normal forward filtering algorithm in terms of positioning accuracy.
出处
《压电与声光》
CAS
CSCD
北大核心
2017年第2期273-276,共4页
Piezoelectrics & Acoustooptics
基金
航空科学基金资助项目(20150852013)
江苏省自然科学基金资助项目(BK20161490)
中央高校基本科研业务专项基金资金资助(NS2015087)
关键词
全球定位系统
惯导
组合导航
滤波算法
正逆向
global position system
inertial navigation
integrated navigation
filtering algorithm
forward and reverse
