摘要
差分卫星导航实时动态(RTK)定位的计算耗时主要取决于定位程序中的卡尔曼滤波实现.卡尔曼滤波实现中有大量的矩阵运算,因此,矩阵的优化技术有可能成为降低RTK计算耗时的有效手段.基于RTK定位算法中卡尔曼状态转移矩阵的特殊性,对卡尔曼的状态变量预测以及状态变量的协方差矩阵预测进行了改进.运动平台实测结果表明,矩阵优化后的RTK定位耗时较优化前减少至1/7倍左右.
The positioning time consuming of the differential global navigation satellite system （DGNSS） real time kinematic （RTK） technology almost depends on the Kalman fil ter implementation. There is a mass of matrix operation in Kalman filter implementation, so matrix operation optimization is an effective mean to reduce time consuming of RTK. The method in this paper improves the matrix operation of Kalman state variable update and it＇s covariance update based on the special Kalman state transfer matrix in RTK positioning algo rithm. The results of motion platforms test show that the improved RTK positioning time consuming is about 7 times less than before.
作者
高科
李慧
赖川
GAO Ke;LI Hui;LAI Chuan(Southwest China Institute of Electronic Tecknology,Ckengdu 610036,Ckina;95806 Troops,Beijing 100076,China)
出处
《全球定位系统》
CSCD
2018年第5期67-69,76,共4页
Gnss World of China
关键词
差分卫星导航
实时动态定位
卡尔曼滤波
矩阵优化
定位耗时
DGNSS
RTK positioning
Kalman filter
matrix operation optimization
positioning time consuming
