GPS/GLONASS Dual System Combined Positioning Algorithm

This article describes the GPS/GLONASS system components, features, navigationdata and modernization program, a comprehensive comparison of both GPS and GLONASSglobal navigation system similarities and differences. Introduced in the general navigation andpositioning error sources need to be considered, and their treatment or correction model, usingLagrange polynomial interpolation, polynomial fitting El Schmitt realized the GPS satelliteposition extrapolation and fitting. Analysis of satellite geometry and accuracy factorscalculated using least squares parameter estimation method to achieve a completed GPSsingle point positioning. The use of fixed-step fourth-order Runge-Kutta numerical integrationmethod and the Lagrange polynomial interpolation algorithm to achieve a GLONASS satellitepositions were extrapolated and fit. On this basis, the use of space-based technology, unifiedcoordinate system GLONASS and GPS, GLONASS ephemeris will be transformed into asingle GPS coordinate system, and set the two-minute difference for two different types ofobservations, and finally, the use of Kalman filter parameter estimation method to completethe GPS/GLONASS positioning system combinations. This paper analyzes the actualobserved data and simulation part of the contents of the combined GPS/GLONASS singlepoint positioning performance is evaluated. the main work are summarized as follows:1) The introduction of GPS single point positioning principle of the method andimplementation. Lagrange polynomial interpolation, polynomial fitting El Schmitt realizedthe GPS satellite position extrapolation and fitting. Comparison shows that fitting accuracy isbetter than the Lagrange Hermite interpolation, Lagrange interpolation amount of time isfaster than the Hermite fit. Analysis of satellite geometry and accuracy factor is calculatedusing least squares method to achieve the parameter estimation. Finally, the analysis of GPSsingle point positioning accuracy.2) describes the position of the GLONASS satellite system is calculated, using the fourthorder fixed step Runge-Kutta numerical integration method and Lagrange polynomialinterpolation algorithm to achieve the GLONASS satellite positions were extrapolated and fit.This GPS single point positioning in the original model, based on the use of MassachusettsInstitute of Technology (MIT) Lincoln Laboratory’s space-based technology, unifiedGLONASS and GPS coordinate system. Will be one of the ephemeris parameters usingtransform into a unified coordinate system transformation, and set the two receiver clock error,respectively, for two types of observations. After the conversion between the given model,derived the data processing for the joint combination of single-point location model.3) analysis of the Kalman estimation method the user position, speed, and thenintroduced the software design module, position solution parameters and the function interface and data transfer protocols. Finally, the measured precision observational data anddownload satellite ephemeris and clock data is poor, the combination of single pointpositioning performance of the model were evaluated. The results found that when a largernumber of GPS satellites and GDOP good time, GLONASS observation data into the modestimprovement of positioning accuracy; GPS satellite number is small, the combinationcompared to single point positioning GPS single point positioning can significantly improvethe convergence after positioning accuracy. This means that when the GPS signal is blocked,GLONASS satellites will be a good supplement.