Research On Positioning Algorithm For BDS/GPS Combined System

With the continuous development of global navigation satellite system,some related products have been used in transportation,marine fisheries,precision agriculture and smart city construction.The different navigation satellite systems can be compatible and interoperable,which establishes the fundation of the combined positioning between systems.Compared to single navigation satellite system,which is often susceptible to poor environmental influence,the combination of multiple navigation satellite systems greatly increases the number of available satellite to solve the problems such as positioning accuracy and reliability.It has become the investigative hotspot of real-time and precise positioning.The thesis focuses on the positioning and solving process of BDS/GPS combined system,which aims to achieve precise positioning and improves positioning accuracy.In the combined method,the traditional scheme does not maximize the advantages of each system.The positioning algorithm based on pseudorange combination is adopted to realize the close combination between BDS and GPS.Firstly,the algorithm introduces the clock difference of system in the geometric pseudorange formula of satellite to receiver,which constructs the pseudorange function expanded by Taylor series to preserve the first-order term;then the algorithm constructs the estimated state vector and design matrix of the combined system;secondly,the combined weighting solution uses a elevation angle model within the system and a posteriori estimation method between systems,which improves the weighting value of the weighted least squares;finally,the solving position coordinates is obtained.The experiment verified the effectiveness of the algorithm by collecting the measured data under the block of the big tree and the house,and the result shows that the accuracy of positioning is improved.In order to meet the requirements of the positioning accuracy in dynamic scenarios,the thesis presents BDS/GPS positioning algorithm based on robust kalman filter.Based on the conventional kalman filter,the algorithm uses the M estimation to improve the robustness.The experiment verified the effectiveness of the algorithm by collecting the measured data under the block and regular motion route,and the result shows that the accuracy of positioning is improved.In addition,the thesis presents BDS/GPS positioning algorithm based on adaptive unscented kalman filter for the nonlinear situation.Based on the unscented kalman filter,the algorithm first introduces the chi-square test to evaluate the system model,and ac-quire the corresponding chi-square test value;then a piecewise linear function between the system noise statistical model and the chi-square test value is constructed to solve the system noise estimated value;finally,the adaptive unscented kalman filter with system noise statistical characteristics is gained.The experiment verified the effectiveness of the algorithm by collecting the measured data under the block and irregular motion route,and the result shows that the accuracy of positioning is improved.