The Global Navigation Satellite System (GNSS) is widely utilized for accurate positioning.One commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network mode....The Global Navigation Satellite System (GNSS) is widely utilized for accurate positioning.One commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network mode.However,this approach can be complex and challenging.Fortunately,The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA),which can enhance positioning accuracy through the precise point positioning (PPP) method.This study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning method.By analyzing a network of 20 GNSS stations in Indonesia,we found that the PPP method using MADOCA products provided favorable positioning estimates.The median discrepancies and the corresponding median absolute deviation (MAD) for easting,northing,and up components were estimated as 9±18 mm,10±9 mm,and 3±40 mm,respectively.These results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks,particularly for orders 0,1,2,and 3,and for a broad spectrum of geoscience monitoring activities.However,considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.展开更多
With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLO...With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLONASS), the single Global Positioning System(GPS) has been gradually expanded into multiple global and regional navigation satellite systems(multi-GNSS/RNSS). In view of differences in these 5 systems, a consolidated multi-GNSS/RNSS precise point positioning(PPP) observation model is deduced in this contribution. In addition, the performance evaluation of PPP for multi-GNSS/RNSS is conducted using a large number of the multi-GNSS experiment(MGEX) station datasets. Experimental results show that multi-GNSS/RNSS can guarantee plenty of visible satellites effectively. Compared with single-system GPS, PDOP, HDOP, and VDOP values of the multi-GNSS/RNSS are improved by 46.8%, 46.5% and 46.3%, respectively. As for convergence time, the static and kinematic PPP of multi-GNSS/RNSS are superior to that of the single-system GPS, whose reliability, availability, and stability drop sharply with the increasing elevation cutoff. At satellite elevation cutoff of 40 °, the single-system GPS fails to carry out continuous positioning because of the insufficient visible satellites, while the multi-GNSS/RNSS PPP can still get positioning solutions with relatively high accuracy, especially in the horizontal direction.展开更多
针对室内、城市峡谷及树荫等遮挡环境使卫星信号中断或变弱,影响北斗三号全球卫星导航系统精密单点定位服务信号(BeiDou Global Satellite Navigation System Precise Point Positioning B2b,BDS-3 PPP-B2b)定位性能的问题,采用卫星导...针对室内、城市峡谷及树荫等遮挡环境使卫星信号中断或变弱,影响北斗三号全球卫星导航系统精密单点定位服务信号(BeiDou Global Satellite Navigation System Precise Point Positioning B2b,BDS-3 PPP-B2b)定位性能的问题,采用卫星导航系统与惯性导航系统(Inertial Navigation System,INS)组合提升定位连续性和精确性。引入BDS-3 PPP-B2b/INS松组合模型,采集开阔环境和卫星遮挡环境数据,分析不同环境下定位系统在位置、速度及姿态方面[JP2]的性能。实验结果表明,相比于BDS-3 PPP-B2b,松组合系统在开阔环境下定位精度提升不明显,而在卫星遮挡环境下提升较明显。组合定位的位置均方根误差(Root Mean Square Error,RMSE)在东向、北向和天向上分别为0.221 m、0.181 m和0.180 m,速度的RMSE在东向、北向和天向上分别为0.078 m·s^(-1)、0.124 m·s^(-1)和0.025 m·s^(-1),横滚角、俯仰角和航向角的RMSE分别为0.157°、0.191°和1.979°。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
差分全球定位系统(difference global positioning system,DGPS)与惯性导航系统(inertial navigation system,INS)所构成的组合定位测姿系统已广泛应用于高精度移动测量领域,但由于需要基准站支持,该系统作业范围有限、作业复杂且成本...差分全球定位系统(difference global positioning system,DGPS)与惯性导航系统(inertial navigation system,INS)所构成的组合定位测姿系统已广泛应用于高精度移动测量领域,但由于需要基准站支持,该系统作业范围有限、作业复杂且成本高。模糊度为浮点解的精密单点定位(precise point positioning,PPP)与INS所构成的组合系统,虽不需要架设基准站,但定位精度有限且收敛时间较长,其原因就在于模糊度为浮点解。针对以上问题,提出将模糊度为固定解的PPP与INS进行紧组合,给出了该新组合详细的观测模型和系统模型。实测车载组合导航实验对新组合进行了验证,结果表明,仅用单台GPS接收机,只需约10余分钟就能获取首次固定解;一旦实现固定,新组合的位置误差迅速由分米级降低到稳定的厘米级。展开更多
Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased es...Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances.To address this issue,a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points(MEEF-CKF)is proposed.The MEEF-CKF behaves a strong robustness against complex nonGaussian noises by operating several major steps,i.e.,regression model construction,robust state estimation and free parameters optimization.More concretely,a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step.The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points(MEEF)under the framework of the regression model.In the MEEF-CKF,a novel optimization approach is provided for the purpose of determining free parameters adaptively.In addition,the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic.The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex nonGaussian noises.展开更多
文摘The Global Navigation Satellite System (GNSS) is widely utilized for accurate positioning.One commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network mode.However,this approach can be complex and challenging.Fortunately,The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA),which can enhance positioning accuracy through the precise point positioning (PPP) method.This study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning method.By analyzing a network of 20 GNSS stations in Indonesia,we found that the PPP method using MADOCA products provided favorable positioning estimates.The median discrepancies and the corresponding median absolute deviation (MAD) for easting,northing,and up components were estimated as 9±18 mm,10±9 mm,and 3±40 mm,respectively.These results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks,particularly for orders 0,1,2,and 3,and for a broad spectrum of geoscience monitoring activities.However,considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.
基金Supported by the National Natural Science Foundation of China (No. 41604018)the Fundamental Research Funds for the Central Universities(No. 2019B17514)+1 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province (No. nos. sjky19_05132019B60114)
文摘With emergence of the BeiDou Navigation Satellite System(BDS), the Galileo Satellite Navigation System(Galileo), the Quasi-Zenith Satellite System(QZSS)and the restoration of the Global Navigation Satellite System(GLONASS), the single Global Positioning System(GPS) has been gradually expanded into multiple global and regional navigation satellite systems(multi-GNSS/RNSS). In view of differences in these 5 systems, a consolidated multi-GNSS/RNSS precise point positioning(PPP) observation model is deduced in this contribution. In addition, the performance evaluation of PPP for multi-GNSS/RNSS is conducted using a large number of the multi-GNSS experiment(MGEX) station datasets. Experimental results show that multi-GNSS/RNSS can guarantee plenty of visible satellites effectively. Compared with single-system GPS, PDOP, HDOP, and VDOP values of the multi-GNSS/RNSS are improved by 46.8%, 46.5% and 46.3%, respectively. As for convergence time, the static and kinematic PPP of multi-GNSS/RNSS are superior to that of the single-system GPS, whose reliability, availability, and stability drop sharply with the increasing elevation cutoff. At satellite elevation cutoff of 40 °, the single-system GPS fails to carry out continuous positioning because of the insufficient visible satellites, while the multi-GNSS/RNSS PPP can still get positioning solutions with relatively high accuracy, especially in the horizontal direction.
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.
文摘差分全球定位系统(difference global positioning system,DGPS)与惯性导航系统(inertial navigation system,INS)所构成的组合定位测姿系统已广泛应用于高精度移动测量领域,但由于需要基准站支持,该系统作业范围有限、作业复杂且成本高。模糊度为浮点解的精密单点定位(precise point positioning,PPP)与INS所构成的组合系统,虽不需要架设基准站,但定位精度有限且收敛时间较长,其原因就在于模糊度为浮点解。针对以上问题,提出将模糊度为固定解的PPP与INS进行紧组合,给出了该新组合详细的观测模型和系统模型。实测车载组合导航实验对新组合进行了验证,结果表明,仅用单台GPS接收机,只需约10余分钟就能获取首次固定解;一旦实现固定,新组合的位置误差迅速由分米级降低到稳定的厘米级。
基金supported by the Fundamental Research Funds for the Central Universities(xzy022020045)the National Natural Science Foundation of China(61976175)。
文摘Traditional cubature Kalman filter(CKF)is a preferable tool for the inertial navigation system(INS)/global positioning system(GPS)integration under Gaussian noises.The CKF,however,may provide a significantly biased estimate when the INS/GPS system suffers from complex non-Gaussian disturbances.To address this issue,a robust nonlinear Kalman filter referred to as cubature Kalman filter under minimum error entropy with fiducial points(MEEF-CKF)is proposed.The MEEF-CKF behaves a strong robustness against complex nonGaussian noises by operating several major steps,i.e.,regression model construction,robust state estimation and free parameters optimization.More concretely,a regression model is constructed with the consideration of residual error caused by linearizing a nonlinear function at the first step.The MEEF-CKF is then developed by solving an optimization problem based on minimum error entropy with fiducial points(MEEF)under the framework of the regression model.In the MEEF-CKF,a novel optimization approach is provided for the purpose of determining free parameters adaptively.In addition,the computational complexity and convergence analyses of the MEEF-CKF are conducted for demonstrating the calculational burden and convergence characteristic.The enhanced robustness of the MEEF-CKF is demonstrated by Monte Carlo simulations on the application of a target tracking with INS/GPS integration under complex nonGaussian noises.
