A new algorithm, called as Double-Epoch Algorithm CDEA) is proposed in GPSrapid positioning using two epoch single frequency phase data in this paper. Firstly, the structurecharacteristic of the normal matrix in GPS r...A new algorithm, called as Double-Epoch Algorithm CDEA) is proposed in GPSrapid positioning using two epoch single frequency phase data in this paper. Firstly, the structurecharacteristic of the normal matrix in GPS rapid positioning is analyzed. Then, in the light of thecharacteristic, based on TIK-HONOV regularization theorem, a new regularizer is designed to mitigatethe ill-condition of the normal matrix. The accurate float ambiguity solutions and their MSEM (MeanSquared Error Matrix) are obtained, u-sing two epoch single frequency phase data. Combined withLAMBDA method, DEA can fix the integer ambiguities correctly and quickly using MSEM instead of thecovariance matrix of the ambiguities. Compared with the traditional methods, DEA can improve theefficiency obviously in rapid positioning. So, the new algorithm has an extensive applicationoutlook in deformation monitoring, pseudokinematic relative positioning and attitude determination,etc.展开更多
The method of cross-ocean GPS long distance rapid static positioning has become one of the main technical means of GPS static positioning away from the mainland. The key technology had been analyzed in-cluding data pr...The method of cross-ocean GPS long distance rapid static positioning has become one of the main technical means of GPS static positioning away from the mainland. The key technology had been analyzed in-cluding data preprocessing and quality control, long distance integer ambiguity resolution and static Kalman filter parameter estimation. Effective data processing method of cross-ocean GPS long baseline rapid static positioning had been proposed. Through the analysis of practical examples of coastal and ocean, the feasibility of cross-ocean GPS long distance rapid static positioning based on the method is testified and verified. The results show that the accuracy of one-hour single baseline static positioning for the 500 - 600 km distance can be better than 10cm in the three-dimensional coordinates ocean environment. , which can suffice static positioning accuracy in the special展开更多
The Low Earth Orbit(LEO)satellites can be used to efectively speed up Precise Point Positioning(PPP)convergence.In this study,180 LEO satellites with a global distribution are simulated to evaluate their contribution ...The Low Earth Orbit(LEO)satellites can be used to efectively speed up Precise Point Positioning(PPP)convergence.In this study,180 LEO satellites with a global distribution are simulated to evaluate their contribution to the PPP convergence.LEO satellites can give more redundant observations and improve satellite geometric distributions,particularly for a single Global Navigation Satellite System(GNSS).The convergence speed of the PPP foat solution using the Global Positioning System(GPS,G)or BeiDou Navigation Satellite System(BDS,C)single system as well as the G/C/Galileo navigation satellite system(Galileo,E)/GLObal NAvigation Satellite System(GLONASS,R)combined system with LEO satellites added is improved by 90.0%,91.0%,and 90.7%,respectively,with respect to the system without LEO satellites added.We introduced LEO observations to assist GNSS in PPP-AR(Ambiguity Resolution)and PPP-RTK(Real Time Kinematic).The success fx rate of a single system is signifcantly improved,and the Time-To-First-Fix(TTFF)of G and G/C/E is reduced by 86.4%and 82.8%,respectively,for the PPP-AR solution.We analyzed the positioning performance of LEO satellite assisted G/C/E PPP-RTK in the reference networks of diferent scales,namely diferent atmospheric delay interpolation accuracies.The success fx rate of the G/C/E combined system is improved from 86.8 to 94.9%,and the TTFF is reduced by 36.8%,with the addition of LEO satellites in the 57 km reference network.In the 110 km reference network,the success fx rate of the G/C/E combined system is improved from 64.0 to 88.6%,and the TTFF is reduced by 32.1%.GNSS PPP-RTK with adding the LEO satellites in the reference networks of diferent scales shows obvious improvement because the atmospheric correlation decreases with increasing distance from the reference networks.展开更多
The combination of fingerprint positioning and 5G(the 5th Generation Mobile Communication Technology)offers broader application prospects for indoor positioning technology,but also brings challenges in real-time perfo...The combination of fingerprint positioning and 5G(the 5th Generation Mobile Communication Technology)offers broader application prospects for indoor positioning technology,but also brings challenges in real-time performance.In this paper,we propose a fingerprint positioning method based on a deep convolutional neural network(DCNN)using a classification approach in a single-base station scenario for massive multiple input multiple outputorthogonal frequency division multiplexing(MIMO-OFDM)systems.We introduce an angle-delay domain fingerprint matrix that simplifies the computation process and increases the location differentiation.The cosine distance is chosen as the fingerprint similarity criterion due to its sensitivity to angular differences.First,the DCNN model is used to determine the sub-area to which the mobile terminal belongs,and then the weighted K-nearest neighbor(WKNN)matching algorithm is used to estimate the position within the sub-area.The positioning performance is simulated in a DeepMIMO indoor environment,showing that the classification DCNN method reduces the positioning time by 77.05%compared to the non-classification method,with only a 1.08%increase in average positioning error.展开更多
文摘A new algorithm, called as Double-Epoch Algorithm CDEA) is proposed in GPSrapid positioning using two epoch single frequency phase data in this paper. Firstly, the structurecharacteristic of the normal matrix in GPS rapid positioning is analyzed. Then, in the light of thecharacteristic, based on TIK-HONOV regularization theorem, a new regularizer is designed to mitigatethe ill-condition of the normal matrix. The accurate float ambiguity solutions and their MSEM (MeanSquared Error Matrix) are obtained, u-sing two epoch single frequency phase data. Combined withLAMBDA method, DEA can fix the integer ambiguities correctly and quickly using MSEM instead of thecovariance matrix of the ambiguities. Compared with the traditional methods, DEA can improve theefficiency obviously in rapid positioning. So, the new algorithm has an extensive applicationoutlook in deformation monitoring, pseudokinematic relative positioning and attitude determination,etc.
文摘The method of cross-ocean GPS long distance rapid static positioning has become one of the main technical means of GPS static positioning away from the mainland. The key technology had been analyzed in-cluding data preprocessing and quality control, long distance integer ambiguity resolution and static Kalman filter parameter estimation. Effective data processing method of cross-ocean GPS long baseline rapid static positioning had been proposed. Through the analysis of practical examples of coastal and ocean, the feasibility of cross-ocean GPS long distance rapid static positioning based on the method is testified and verified. The results show that the accuracy of one-hour single baseline static positioning for the 500 - 600 km distance can be better than 10cm in the three-dimensional coordinates ocean environment. , which can suffice static positioning accuracy in the special
基金the program of National Natural Science Foundation of China(Grant Nos.41974032,42274019).
文摘The Low Earth Orbit(LEO)satellites can be used to efectively speed up Precise Point Positioning(PPP)convergence.In this study,180 LEO satellites with a global distribution are simulated to evaluate their contribution to the PPP convergence.LEO satellites can give more redundant observations and improve satellite geometric distributions,particularly for a single Global Navigation Satellite System(GNSS).The convergence speed of the PPP foat solution using the Global Positioning System(GPS,G)or BeiDou Navigation Satellite System(BDS,C)single system as well as the G/C/Galileo navigation satellite system(Galileo,E)/GLObal NAvigation Satellite System(GLONASS,R)combined system with LEO satellites added is improved by 90.0%,91.0%,and 90.7%,respectively,with respect to the system without LEO satellites added.We introduced LEO observations to assist GNSS in PPP-AR(Ambiguity Resolution)and PPP-RTK(Real Time Kinematic).The success fx rate of a single system is signifcantly improved,and the Time-To-First-Fix(TTFF)of G and G/C/E is reduced by 86.4%and 82.8%,respectively,for the PPP-AR solution.We analyzed the positioning performance of LEO satellite assisted G/C/E PPP-RTK in the reference networks of diferent scales,namely diferent atmospheric delay interpolation accuracies.The success fx rate of the G/C/E combined system is improved from 86.8 to 94.9%,and the TTFF is reduced by 36.8%,with the addition of LEO satellites in the 57 km reference network.In the 110 km reference network,the success fx rate of the G/C/E combined system is improved from 64.0 to 88.6%,and the TTFF is reduced by 32.1%.GNSS PPP-RTK with adding the LEO satellites in the reference networks of diferent scales shows obvious improvement because the atmospheric correlation decreases with increasing distance from the reference networks.
基金supported by the National Key Research and Development Program of China(No.2022YFC3801000)the Fundamental Research Funds for the Central Universities(No.2242022k60001,2242023K40015).
文摘The combination of fingerprint positioning and 5G(the 5th Generation Mobile Communication Technology)offers broader application prospects for indoor positioning technology,but also brings challenges in real-time performance.In this paper,we propose a fingerprint positioning method based on a deep convolutional neural network(DCNN)using a classification approach in a single-base station scenario for massive multiple input multiple outputorthogonal frequency division multiplexing(MIMO-OFDM)systems.We introduce an angle-delay domain fingerprint matrix that simplifies the computation process and increases the location differentiation.The cosine distance is chosen as the fingerprint similarity criterion due to its sensitivity to angular differences.First,the DCNN model is used to determine the sub-area to which the mobile terminal belongs,and then the weighted K-nearest neighbor(WKNN)matching algorithm is used to estimate the position within the sub-area.The positioning performance is simulated in a DeepMIMO indoor environment,showing that the classification DCNN method reduces the positioning time by 77.05%compared to the non-classification method,with only a 1.08%increase in average positioning error.
