The global navigation satellite system(GNSS)positioning chip has become an important sensor for navigation and positioning with smartphones.With the continuous development and deepening of the information and intelligent society,the demand for high-precision positioning services for mobile phones has been increasing.In this paper,by analyzing the correlation between pseudorange residuals and altitude angle,C/N0,and original GNSS observation information of mobile phones,it is found that the ReceivedSvTimeUncertaintyNanos in the original GNSS obser-vation information of mobile phones has a higher correlation with pseudorange residuals compared with C/N0.Therefore,a stochastic model construction method for GNSS precision positioning based on ridge regression and raw observation information of smartphones is proposed.By con-structing a ridge regression model with the original mobile phone observation information as the feature variables,training the model with the Google open dataset,the learning of the relationship between the pseudorange residuals and various feature variables is performed,and then predicting the pseudorange noise online,which is used as the basis for weighting observations in GNSS posi-tioning.Finally,real-time kinematic positioning(RTK)and precise point positioning(PPP)ex-periments are carried out to verify the positioning performance of the new weighting method,and the experimental results show that the positioning accuracy of the new weighting method is im-proved by an average of 24.9％,44.8％,and 39.3％,respectively,compared with that of the tra-ditional C/N0 weighting method in the three sets of experiments.
关键词
随机模型/岭回归/GNSS/定权方法/实时动态定位/精密单点定位
Key words
Stochastic model/Ridge regression/Global navigation satellite system(GNSS)/Weighting method/Real-time kinematic/Precise point positioning
维普
万方数据