Realization And Optimization Of Navigation Reveiver Positioning Based On Kalman In Complex Dynamic Environment

The rapid development in the aviation,aerospace and other fields with complex dynamic poses higher requirements for the positioning capability of satellite navigation receivers.This thesis studied the application and optimization of kalman filter algorithm in the satellite navigation receiver positioning calculation with complex dynamic environment.In this thesis,the navigation receiver position and speed calculation and kalman filter algorithm were studied theoretically at first.Secondly,on the basis of theory,this thesis discretizes and linearizes the kalman filter for the continuous nonlinearity of navigation receiver positioning system.And the user motion model,system model and observation model under the condition of low dynamic environment and complex dynamic environment were designed.This thesis discussed the setting of error covariance matrix and gave the design of navigation and positioning solution module based on kalman filter.The project was implemented on the project based on C language.The module was tested and verified in the static environment test platform and the complex dynamic enviroment test platform provided by the simulation source.The kalman filter's navigation and location solution module researched and implemented in this thesis had been directly applied to engineering projects and achieved good effect.In order to meet the requirements of handling multi-system signal resources,this thesis adjusted the navigation and positioning module for the differences among systems so that the module can process signals of two system,the global positioning system(GPS)and BeiDou Navigation Satellite System(BDS).This thesis made further research in the stability problem existing in kalman filter.In order to solve the problem of divergence of kalman filter in complex dynamic environment,a judgment method based on the new information sequence was proposed and an optimization scheme based on weighting was proposed and implemented.Finally,the board-level test proved that,after judging the filter divergence,weighting the state error covariance matrix,and recalculating kalman filter gain,can play a role in improving positioning accuracy.