Algorithm And Implementation Of GNSS Carrier Phase Difference Based On EKF

With the opening of the Beidou-3 system,GNSS multi-system multi-frequency combined positioning has become a development trend in the field of navigation and positioning,and carrier phase differential positioning with multi-system and multifrequency data fusion has become one of the key technologies for high-precision positioning.Aiming at the problem of the large number of nonlinear equations in GNSS combined positioning and the large amount of calculation,the focus is on the theory and implementation of the Extended Kalman Filter(EKF)algorithm in GNSS carrier phase differential positioning.The main research work and results are as follows:(1)The difference between GPS system and BDS system in time system and coordinate system is analyzed in detail.The satellite position of GPS system and BDS system is deduced and calculated.The time system and coordinate system are normalized to provide the basis for GPS/BDS combined positioning.(2)The mathematical models of pseudorange single point positioning,carrier phase difference positioning,satellite-related,propagation path-related and receiver-related error sources and their correction models in GPS/BDS combined positioning are studied and established.(3)The EKF algorithm of GNSS carrier phase difference is mainly studied.According to the characteristics of GNSS combined positioning,the mathematical model of EKF algorithm with single difference ambiguity to estimate the floating point solution is analyzed.The improved robust EKF mathematical model of IGG III robust model is established.The height angle weight model and the signal-to-noise ratio weight model are studied.The entropy weight method is used to combine the two models,and the improved robust EKF mathematical model is added to estimate the floating point solution.(4)Based on the Python language and process-oriented concept,a multi-system and multi-frequency GNSS carrier phase difference positioning program is written according to the algorithm in this paper.The standard EKF algorithm and the improved robust EKF algorithm with joint weighting of elevation angle and signal-to-noise ratio are realized.The algorithm is verified by the measured data of the static control network.The results show that the GPS/BDS dual-frequency positioning model has the best accuracy compared with the single system positioning.The RMS values of the three baselines are better than 21.50 mm,40.10 mm and 10.20 mm in the three-dimensional coordinate direction.The GPS single frequency,BDS single frequency and GPS/BDS dualfrequency positioning model of the improved robust EKF are used to calculate the baseline data of artificially adding gross errors.Compared with the standard EKF positioning model,the maximum robust improvement rates are 92.09%,86.47% and0.12%,it verifies the robustness of the improved anti-error EKF algorithm in singlesystem and single-frequency,which can provide an effective robustness method for lowcost receivers.Figure 14;Table 10;Reference 61...