Satellite positioning technology has been widely used in all kinds of military and civil land, marine, space and aeronautical target positioning tasks, naviga tion activities and accurate surveying measurements since ...Satellite positioning technology has been widely used in all kinds of military and civil land, marine, space and aeronautical target positioning tasks, naviga tion activities and accurate surveying measurements since 90 s in the last cen tury due to its advantage in providing all-weather, real-time, three dimensional and high precision positioning information, as well as speed and accurate timing information. By now, it has already formed a new hi-tech industry basically.This paper briefly reviews the development of the global satellite positioning and navigation technologies including the basic information of China's "Plough navigation system", introduces the history of satellite positioning technology and its major application fields as well as the status quo of this being industri alized trade in China, gives an account of the writers' vision for the application and prospect of the satellite positioning technologies in China, and approaches the tactics and stresses of the satellite positioning technology's application and its industrialization future in China.展开更多
Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic acti...Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic activity the Total Electron Content(TEC)have significant variations in both time and space.These temporal and spatial TEC variations driven by interplanetary space weather conditions such as solar and geomagnetic activities can degrade the communication and navigation links of GPS.Hence,in this paper,performance of TEC forecasting models based on Neural Networks(NN)have been evaluated to forecast(1-h ahead)ionospheric TEC over equatorial low latitude Bengaluru e12:97+N;77:59+ET,Global Navigation Satellite System(GNSS)station,India.The VTEC data is collected for 2009 e2016(8 years)during current 24 th solar cycle.The input space for the NN models comprise the solar Extreme UV flux,F10.7 proxy,a geomagnetic planetary A index(AP)index,sunspot number(SSN),disturbance storm time(DST)index,solar wind speed(Vsw),solar wind proton density(Np),Interplanetary Magnetic Field(IMF Bz).The performance of NN based TEC forecast models and International Reference Ionosphere,IRI-2016 global TEC model has evaluated during testing period,2016.The NN based model driven by all the inputs,which is a NN unified model(NNunq)has shown better accuracy with Mean Absolute Error(MAE)of 3.15 TECU,Mean Square Deviation(MSD)of 16.8 and Mean Absolute Percentage Error(MAPE)of 19.8%and is 1 e25%more accurate than the other NN based TEC forecast models(NN1,NN2 and NN3)and IRI-2016 model.NNunq model has less Root Mean Square Error(RMSE)value 3.8 TECU and highest goodness-of-fit(R2)with 0.85.The experimental results imply that NNunq/NN1 model forecasts ionospheric TEC accurately across equatorial low-latitude GNSS station and IRI-2016 model performance is necessarily improved as its forecast accuracy is limited to 69 e70%.展开更多
Soil moisture is a key parameter in agricultural irrigation.The L band（1.58GHz）on board global position system（GPS） satellite is well suited for monitoring the change of soil moisture.In order to investigate the p...Soil moisture is a key parameter in agricultural irrigation.The L band（1.58GHz）on board global position system（GPS） satellite is well suited for monitoring the change of soil moisture.In order to investigate the potential of retrieving soil moisture using the L-band GPS bistatic radar,this paper analyzed a retrieval method by using field experiment data.In order to investigate the relationship between the soil moisture（corresponding roughly to the 05cm top soil layer） and the signalto-noise ratio(Pr-SNR) to the direct GPS signal-to-noise ratio(Pd-SNR),an experiment was conducted in Hulunber grassland of China in 2009 and 2011.Six field sites in the soil moisture experiment were utilized to analyze the relationship between soil moisture and the ratio of Pr-SNR to Pd-SNR and the square of correlation coefficient was about 0.9 when the surface type was known and the elevation angle of the satellite ranged from 65 to 85 degrees approximately.The analysis shows that ratio of Pr-SNR to P（d-SNR） can be used to monitor the soil moisture,because the ratio of P（r-SNR） to P（d-SNR） maximized the elimination of the influence of different signals from different GPS satellites.The estimation accuracy could be improved if we make full use of the empirical knowledge on elevation angles of GPS satellites and ground roughness of different surface types.展开更多
The availability of raw Global Navigation Satellite System(GNSS)measurements from Android smart devices gives new possibilities for precise positioning solutions,e.g.,Precise Point Positioning(PPP).However,the accurac...The availability of raw Global Navigation Satellite System(GNSS)measurements from Android smart devices gives new possibilities for precise positioning solutions,e.g.,Precise Point Positioning(PPP).However,the accuracy of the PPP with smart devices currently is a few meters due to the poor quality of the raw GNSS measurements in a kinematic scenario and in urban environments,particularly when the smart devices are placed inside vehicles.To promote the application of GNSS PPP for land vehicle navigation with smart devices,this contribution studies the real-time PPP with smartphones.For data quality analysis and positioning performance validation,two vehicle-based kinematic positioning tests were carried out using two Huawei Mate30 smartphones and two Huawei P40 smartphones with different installation modes:the vehicle-roof mode with smartphones mounted on the top roof outside the vehicle,and the dashboard mode with smartphones stabilized on the dashboard inside the vehicle.To realize high accuracy positioning,we proposed a real-time smartphone PPP method with the data processing strategies adapted for smart devices.Positioning results show that the real-time PPP can achieve the horizontal positioning accuracy of about 1–1.5 m in terms of root-mean-square and better than 2.5 m at the 95th percentile for the vehicle-based kinematic positioning with the experimental smartphones mounted on the dashboard inside the vehicle,which is the real scenario in vehicle navigation.展开更多
An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） s...An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） suffers the problem for which the uncertainty of the statistical properties to dynamic and measurement models will degrade the performance.In this research, an Adaptive Interacting Multiple Model（AIMM） filter is developed to enhance performance. The soft-switching property of Interacting Multiple Model（IMM） algorithm allows the adaptation between two levels of process noise, namely lower and upper bounds of the process noise. In particular, the Sage adaptive filtering is applied to adapt the measurement covariance on line. In addition, a classified measurement update strategy is utilized, which updates the pseudorange and Doppler observations sequentially. A field experiment was conducted to validate the proposed algorithm, the pseudorange and Doppler observations from Global Positioning System（GPS） and Bei Dou Navigation Satellite System（BDS） were post-processed in differential mode.The results indicate that decimeter-level positioning accuracy is achievable with AIMM for GPS/INS and GPS/BDS/INS configurations, and the position accuracy is improved by 35.8%, 34.3% and 33.9% for north, east and height components, respectively, compared to the CEKF counterpartfor GPS/BDS/INS. Degraded performance for BDS/INS is obtained due to the lower precision of BDS pseudorange observations.展开更多
文摘Satellite positioning technology has been widely used in all kinds of military and civil land, marine, space and aeronautical target positioning tasks, naviga tion activities and accurate surveying measurements since 90 s in the last cen tury due to its advantage in providing all-weather, real-time, three dimensional and high precision positioning information, as well as speed and accurate timing information. By now, it has already formed a new hi-tech industry basically.This paper briefly reviews the development of the global satellite positioning and navigation technologies including the basic information of China's "Plough navigation system", introduces the history of satellite positioning technology and its major application fields as well as the status quo of this being industri alized trade in China, gives an account of the writers' vision for the application and prospect of the satellite positioning technologies in China, and approaches the tactics and stresses of the satellite positioning technology's application and its industrialization future in China.
基金Subject National high technology Research And Development Program (2005AA1Z1192)Doctor Project Scientific Research Fund of Taiyuan Science and Technology (200779)
基金the research project titled"Implementation of Deep Learning Algorithms to Develop Web based Ionospheric Time Delays Forecasting System over Indian Region using Ground based GNSS and NAVigation with Indian Constellation(NAVIC)observations"sponsored by Science&Engineering Research Board(SERB)(A statutory body of the Department of Science&Technology,Government of India,New Delhi,India,vide sanction order No:ECR/2018/001701Department of Science and Technology,New Delhi,India for funding this research through SR/FST/ESI-130/2013(C)FIST program
文摘Global Positioning System(GPS)services could be improved through prediction of ionospheric delays for satellite-based radio signals.With respect to latitude,longitude,local time,season,solar cycle and geomagnetic activity the Total Electron Content(TEC)have significant variations in both time and space.These temporal and spatial TEC variations driven by interplanetary space weather conditions such as solar and geomagnetic activities can degrade the communication and navigation links of GPS.Hence,in this paper,performance of TEC forecasting models based on Neural Networks(NN)have been evaluated to forecast(1-h ahead)ionospheric TEC over equatorial low latitude Bengaluru e12:97+N;77:59+ET,Global Navigation Satellite System(GNSS)station,India.The VTEC data is collected for 2009 e2016(8 years)during current 24 th solar cycle.The input space for the NN models comprise the solar Extreme UV flux,F10.7 proxy,a geomagnetic planetary A index(AP)index,sunspot number(SSN),disturbance storm time(DST)index,solar wind speed(Vsw),solar wind proton density(Np),Interplanetary Magnetic Field(IMF Bz).The performance of NN based TEC forecast models and International Reference Ionosphere,IRI-2016 global TEC model has evaluated during testing period,2016.The NN based model driven by all the inputs,which is a NN unified model(NNunq)has shown better accuracy with Mean Absolute Error(MAE)of 3.15 TECU,Mean Square Deviation(MSD)of 16.8 and Mean Absolute Percentage Error(MAPE)of 19.8%and is 1 e25%more accurate than the other NN based TEC forecast models(NN1,NN2 and NN3)and IRI-2016 model.NNunq model has less Root Mean Square Error(RMSE)value 3.8 TECU and highest goodness-of-fit(R2)with 0.85.The experimental results imply that NNunq/NN1 model forecasts ionospheric TEC accurately across equatorial low-latitude GNSS station and IRI-2016 model performance is necessarily improved as its forecast accuracy is limited to 69 e70%.
基金Supported by the National Key Basic Research Program of China(No.2010CB951503,2013BAC03B00)
文摘Soil moisture is a key parameter in agricultural irrigation.The L band（1.58GHz）on board global position system（GPS） satellite is well suited for monitoring the change of soil moisture.In order to investigate the potential of retrieving soil moisture using the L-band GPS bistatic radar,this paper analyzed a retrieval method by using field experiment data.In order to investigate the relationship between the soil moisture（corresponding roughly to the 05cm top soil layer） and the signalto-noise ratio(Pr-SNR) to the direct GPS signal-to-noise ratio(Pd-SNR),an experiment was conducted in Hulunber grassland of China in 2009 and 2011.Six field sites in the soil moisture experiment were utilized to analyze the relationship between soil moisture and the ratio of Pr-SNR to Pd-SNR and the square of correlation coefficient was about 0.9 when the surface type was known and the elevation angle of the satellite ranged from 65 to 85 degrees approximately.The analysis shows that ratio of Pr-SNR to P（d-SNR） can be used to monitor the soil moisture,because the ratio of P（r-SNR） to P（d-SNR） maximized the elimination of the influence of different signals from different GPS satellites.The estimation accuracy could be improved if we make full use of the empirical knowledge on elevation angles of GPS satellites and ground roughness of different surface types.
基金National Natural Science Foundation of China(42104027)cooperative research project with Huawei,the Alliance of International Science Organizations(ANSO-CRKP-2020-12)Youth Innovation Promotion Association and Future Star Program of the Chinese Academy of Sciences.
文摘The availability of raw Global Navigation Satellite System(GNSS)measurements from Android smart devices gives new possibilities for precise positioning solutions,e.g.,Precise Point Positioning(PPP).However,the accuracy of the PPP with smart devices currently is a few meters due to the poor quality of the raw GNSS measurements in a kinematic scenario and in urban environments,particularly when the smart devices are placed inside vehicles.To promote the application of GNSS PPP for land vehicle navigation with smart devices,this contribution studies the real-time PPP with smartphones.For data quality analysis and positioning performance validation,two vehicle-based kinematic positioning tests were carried out using two Huawei Mate30 smartphones and two Huawei P40 smartphones with different installation modes:the vehicle-roof mode with smartphones mounted on the top roof outside the vehicle,and the dashboard mode with smartphones stabilized on the dashboard inside the vehicle.To realize high accuracy positioning,we proposed a real-time smartphone PPP method with the data processing strategies adapted for smart devices.Positioning results show that the real-time PPP can achieve the horizontal positioning accuracy of about 1–1.5 m in terms of root-mean-square and better than 2.5 m at the 95th percentile for the vehicle-based kinematic positioning with the experimental smartphones mounted on the dashboard inside the vehicle,which is the real scenario in vehicle navigation.
基金co-supported by the National Key Research and Development Program of China(No.2016YFC0803103)Beijing Advanced Innovation Center for Future Urban Design(No.UDC2016050100)Beijing Postdoctoral Research Foundation
文摘An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） suffers the problem for which the uncertainty of the statistical properties to dynamic and measurement models will degrade the performance.In this research, an Adaptive Interacting Multiple Model（AIMM） filter is developed to enhance performance. The soft-switching property of Interacting Multiple Model（IMM） algorithm allows the adaptation between two levels of process noise, namely lower and upper bounds of the process noise. In particular, the Sage adaptive filtering is applied to adapt the measurement covariance on line. In addition, a classified measurement update strategy is utilized, which updates the pseudorange and Doppler observations sequentially. A field experiment was conducted to validate the proposed algorithm, the pseudorange and Doppler observations from Global Positioning System（GPS） and Bei Dou Navigation Satellite System（BDS） were post-processed in differential mode.The results indicate that decimeter-level positioning accuracy is achievable with AIMM for GPS/INS and GPS/BDS/INS configurations, and the position accuracy is improved by 35.8%, 34.3% and 33.9% for north, east and height components, respectively, compared to the CEKF counterpartfor GPS/BDS/INS. Degraded performance for BDS/INS is obtained due to the lower precision of BDS pseudorange observations.
