摘要
在动态载体如汽车、船舶或静态载体如桥梁、房屋的姿态推算中,使用全球导航卫星系统(global navigation satellitesystem,GNSS)进行载体测向,比起使用惯性传感器成本较低;且随时间不会累积误差。针对在多天线基线解算时存在的接收机时钟不同步造成基线解算精度下降,以及载体运动过程中多径和周跳等造成的误差问题,提出了一种基于参考天线位置修正的扩展卡尔曼滤波(extended Kalman filter,EKF)算法。根据载体移动速度和接收机之间的时钟差对每一历元载体参考天线位置矫正,提高基线解算的精度,从而提高姿态角精度。基线解算采用实时动态定位技术(real time kinematic,RTK),根据接收机给出的载波相位观测量,在参考天线和其他天线之间做双差建立观测方程,求解出基线向量。将得到的多组基线向量利用最小二乘法求解出姿态角。根据实际测试表明,该方法在基线长度不超过1. 5 m的情况下,静态航向角和俯仰角精度达到0. 2°,低动态情况下航向角精度达到0. 2°,俯仰角精度达到0. 3°。
To determing the attitude of moving platform such as vehicles and ships,or static carrier such as bridge and building,the use of global navigation satellite system( GNSS) is lower cost and the errors of attitude parameters won’t accumulate with time compare with inertial sensors. This case study aims to demonstrate an antenna-position-correction algorithm based on extended Kalman filter( EKF),to solve the error caused by the synchronization of the receiver clock and multi-path effect or cycle slips during the movement of the platform. By correcting the position of reference antenna of each epoch,the accuracy of baseline and attitude angle could be improved. At the same time,using real time dynamic( RTK) positioning technique to calculate the vector of baseline. According to the observation of carrier-phase given by the receiver,the double difference between reference antenna is made to establish the observation equation. The obtained sets of baseline vectors are solved by least squares method to evaluate attitude angle. The experiment results indicate that in the static mode,the precision of the static heading and pitching angle is 0. 2 degrees under the condition which baseline length less than 1. 5 meters. And under the low dynamic mode,the precision of the heading angle is 0. 2 degrees and the pitch angle accuracy reaches 0. 3 degrees.
作者
王守华
李云柯
纪元法
孙希延
WANG Shou-hua;LI Yun-ke;JI Yuan-fa;SUN Xi-yan(Guangxi Key Laboratory of Precision Navigation Technology and Application,National and Local Joint Engineering Research Center of Satellite Navigation and Location Awareness,Guilin 541004,China)
出处
《科学技术与工程》
北大核心
2019年第7期115-119,共5页
Science Technology and Engineering
基金
广西精密导航技术与应用重点实验室主任基金(DH201803)
桂林电子科技大学研究生教育创新计划项目(2018YJCX28)
国家重点研发计划(2018YFB0505103)
广西科技厅项目(桂科AA17202033)资助
关键词
天线测姿
多基线
扩展卡尔曼滤波
钟差位置修正
attitude determination
multi baseline
Kalman filter
clock bias and correction
