为了分析当前GPS(Global Positioning System)、Galileo(Galileo Navigation Satellite System)和BDS-3(Beidou Navigation Satellite System with Global Coverage)广播星历的精度,详细分析研究了各种偏差改正及消除方法,并尽可能地消...为了分析当前GPS(Global Positioning System)、Galileo(Galileo Navigation Satellite System)和BDS-3(Beidou Navigation Satellite System with Global Coverage)广播星历的精度,详细分析研究了各种偏差改正及消除方法,并尽可能地消除了系统误差和粗差对评估结果的影响。选取2021-11-01/12-31共61天MGEX(multi-GNSS experiment)发布的多系统混合广播星历与武汉大学分析中心发布的事后精密星历数据进行实验,对GPS、Galileo和BDS-3近期广播星历精度进行对比分析,实验结果表明:3个系统广播星历整体精度由高到低依次是Galileo、BDS-3和GPS,其空间信号测距误差的RMS(root mean square)分别优于0.17、0.25和0.37 m,整体轨道精度的RMS分别优于0.17、0.12和0.25 m,BDS-3广播星历的轨道精度最高,钟差误差的RMS分别优于0.15、0.23和0.27 m,Galileo广播星历的钟差精度最高。对于GPS卫星的广播星历,blockⅢA卫星钟差和轨道精度均优于其他GPS类型卫星。展开更多
When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the feature...When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.展开更多
Considering the need of target positioning,a remote positioning system is designed based on global positioning system(GPS)and general packet radio service(GPRS);The data collection terminal is based on microcontroller...Considering the need of target positioning,a remote positioning system is designed based on global positioning system(GPS)and general packet radio service(GPRS);The data collection terminal is based on microcontroller unit(MCU)PIC24FV301.It uses GPRS network to create wireless link and transmits GPS source information which is collected by LEA-5H board to monitor center on the Internet.The monitor center obtains the target information through processing and analysis of the calculated data.Actual operation results indicate that the designed system has excellent performance and achieves the goal of the remote location.展开更多
文摘为了分析当前GPS(Global Positioning System)、Galileo(Galileo Navigation Satellite System)和BDS-3(Beidou Navigation Satellite System with Global Coverage)广播星历的精度,详细分析研究了各种偏差改正及消除方法,并尽可能地消除了系统误差和粗差对评估结果的影响。选取2021-11-01/12-31共61天MGEX(multi-GNSS experiment)发布的多系统混合广播星历与武汉大学分析中心发布的事后精密星历数据进行实验,对GPS、Galileo和BDS-3近期广播星历精度进行对比分析,实验结果表明:3个系统广播星历整体精度由高到低依次是Galileo、BDS-3和GPS,其空间信号测距误差的RMS(root mean square)分别优于0.17、0.25和0.37 m,整体轨道精度的RMS分别优于0.17、0.12和0.25 m,BDS-3广播星历的轨道精度最高,钟差误差的RMS分别优于0.15、0.23和0.27 m,Galileo广播星历的钟差精度最高。对于GPS卫星的广播星历,blockⅢA卫星钟差和轨道精度均优于其他GPS类型卫星。
基金National Natural Science Foundation of China(Nos.61662070,61363059)Youth Science Fund Project of Lanzhou Jiaotong University(No.2018036)。
文摘When using global positioning system/BeiDou navigation satellite(GPS/BDS)dual-mode navigation system to locate a train,Kalman filter that is used to calculate train position has to be adjusted according to the features of the dual-mode observation.Due to multipath effect,positioning accuracy of present Kalman filter algorithm is really low.To solve this problem,a chaotic immune-vaccine particle swarm optimization_extended Kalman filter(CIPSO_EKF)algorithm is proposed to improve the output accuracy of the Kalman filter.By chaotic mapping and immunization,the particle swarm algorithm is first optimized,and then the optimized particle swarm algorithm is used to optimize the observation error covariance matrix.The optimal parameters are provided to the EKF,which can effectively reduce the impact of the observation value oscillation caused by multipath effect on positioning accuracy.At the same time,the train positioning results of EKF and CIPSO_EKF algorithms are compared.The eastward position errors and velocity errors show that CIPSO_EKF algorithm has faster convergence speed and higher real-time performance,which can effectively suppress interference and improve positioning accuracy.
文摘Considering the need of target positioning,a remote positioning system is designed based on global positioning system(GPS)and general packet radio service(GPRS);The data collection terminal is based on microcontroller unit(MCU)PIC24FV301.It uses GPRS network to create wireless link and transmits GPS source information which is collected by LEA-5H board to monitor center on the Internet.The monitor center obtains the target information through processing and analysis of the calculated data.Actual operation results indicate that the designed system has excellent performance and achieves the goal of the remote location.
