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
The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the...The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.展开更多
为比较分析城市道路观测环境下BDS-3/GPS组合RTK测量性能,探讨一种基于卡尔曼滤波算法的RTK测量模型。在统一BDS-3/GPS组合RTK测量时空基准的基础上,建立RTK观测方程模型,利用LAMBDA算法快速确定双差整周模糊度,并基于卡尔曼滤波算法求...为比较分析城市道路观测环境下BDS-3/GPS组合RTK测量性能,探讨一种基于卡尔曼滤波算法的RTK测量模型。在统一BDS-3/GPS组合RTK测量时空基准的基础上,建立RTK观测方程模型,利用LAMBDA算法快速确定双差整周模糊度,并基于卡尔曼滤波算法求解RTK观测方程模型测量结果;基于Visual Studio 2020平台,运用C/C++编程语言,设计和开发RTK数据处理软件(KalRTK),并比较分析BDS-3/GPS组合RTK测量结果。通过城市道路实测数据分析结果表明,BDS-3系统沿东西向跟踪卫星能力要略弱于GPS系统;BDS-3/GPS组合RTK测量的平面精度与高程精度均优于1.6cm,点位精度优于2.2cm,与GPS双频RTK测量精度基本相当,但优于BDS-3双频RTK测量精度。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
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supported by“The National Key Research and Development Program of China(No.2020YFA0713502)”“The National Natural Science Foundation of China(No.41874039)”+1 种基金“Jiangsu National Science Foundation(No.BK20191342)”“Fundamental Research Funds for the Central Universities(No.2019ZDPY-RH03)”。
文摘The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.
文摘为比较分析城市道路观测环境下BDS-3/GPS组合RTK测量性能,探讨一种基于卡尔曼滤波算法的RTK测量模型。在统一BDS-3/GPS组合RTK测量时空基准的基础上,建立RTK观测方程模型,利用LAMBDA算法快速确定双差整周模糊度,并基于卡尔曼滤波算法求解RTK观测方程模型测量结果;基于Visual Studio 2020平台,运用C/C++编程语言,设计和开发RTK数据处理软件(KalRTK),并比较分析BDS-3/GPS组合RTK测量结果。通过城市道路实测数据分析结果表明,BDS-3系统沿东西向跟踪卫星能力要略弱于GPS系统;BDS-3/GPS组合RTK测量的平面精度与高程精度均优于1.6cm,点位精度优于2.2cm,与GPS双频RTK测量精度基本相当,但优于BDS-3双频RTK测量精度。
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.
