Tracking And Multipath Estimation Algorithm Of GPS Signal Based On Kalman Filtering

The GPS signal strength decaying seriously because of penetration loss、reflection loss、diffraction loss、signal fading and some other processes When going through the indoorenvironments(such as rooms or cities or forests or some complex environments and so on)，andin the influences of multipath，the SNR and tracking precision of the signal is very low，resultingin the carrier tracking loop even lock-lose or does not work correctly.so in this paper, to solvethe problems above，the GPS propagation model、Multipath signal estimate and compensation inindoor environments were studied.This thesis first introducs the structure of GPS signal and the architecture and principles ofGPS software receiver，then analyze the differences of tracking algorithm between traditionalKalman filtering loop and the improved Kalman filtering loop.In order to solve the problem thatthe traditional receiver could not track the weak signal accuratly, using the adaptive Kalmanfilter replace the Kalman filter to estimate the tracking error.Design the adaptive filter algorithmbased on the feature that the innovation of the optimal Kalman filter should be zero mean whitenoise to make the capability of the filter parameters and the precision of the tracking signal betteradapted to the environment.At the same time through the analyses of GPS signals，Using themaximum likelihood estimate based on Kalman filtering algorithm to estimate and compensatethe amplitude and phase of Multipath signals to make the tracking results more accurate.Finally，this paper simulated the tracking algorithm of traditional GPS receiver andimproved GPS receiver，the results demonstrate that, the tracking precision and the capabilityof the improved receiver are obviously improved.