Research On Tracking Technique Of Satellite Navigation Signals In High Dynamic Applications

The Phase-locked loop (PLL) is used in GPS receivers to track an incoming signal and to provide accurate carrier phase measurements. Some performances, such as noise performance (the ability to filter out noise), high dynamic tracking performance (the ability to track signal whose carrier frequency varies rapidly) and tracking accruacy are criterias to evaluate the PLL. However, these criterias are not only related to each other but also always conflicted. Tracking accuracy is related to noise performance which is reprented by static error. That means better noise performance is with less static error and higher accuracy. In addition, tracking performance is to some extnet effected by the high dynamic tracking ability. If the tracking loop can not track the dynamic of the signal, the tracking accuracy becomen worse and the dynamic error emerges. The static error and dynamic error are contradictory in term of bandwith. Narrow loop bandwith can reduce the static error when the dynamic error increases. In high dynamic situations, traditional PLL has to sacrafice tracking accuracy to satisfy the requirement of dynamic performance. With this compromise, traditional PLL could track high dynamic signal. Thus, this thesis focus on the conflict,i.e the different bandwith requirement by the PLL static error and dynamic error. In order to resolve this bandwith conflict and improve PLL tracking performance under high dynamic circumstance, this thesis study on how the tracking loop can not lose racking accuracy and can track the high dynamic signal at the same timeThree methods, aiming at the loop filter, loop noise and loop bandwith respectively which are the three main factors affecting the PLL performance, are investigated to improve PLL tracking performance in high dynamic applications: a Kalman filter-based tracking algorithm, application of a wavelet denoising technique in PLL, and an adaptive bandwidth algorithm. About the loop filter affecting the PLL performance, the Uncented Kalman filter-based tracking algorithm, replacing of the traditional PLL, is used to resolve the bandwith confilct between static and dynamic error. About the loop noise affecting the PLL performance, the wavelet de-noising technique is emploied to effectively decreases the noise level and allows broadening of the PLL bandwidth to track high dynamics signals. About the loop bandwith affecting the loop performace, the adaptive bandwidth PLL algorithm adapts the bandwith of the PLL according to the estimation of the incoming signal dynamics and caculate the optimum bandwith with iteration processing based on the SNR so as to improve the tracking performance under high dynamic conditions. To analyze the performance improvement by the three proposed algorithms, simulation is conducted with different dynamic models and parameters in terms of signal-to-noise ratios and dynamic variations using simulating GPS signals in Matlab. The proposed algorithms are found to be better in noise performance, dynamic performance and tracking performance under high dynamic variations. PLL based on UKF does not only have better tracking performance but also has better ablity to filtering noise and dynamic tracking ability. However, since the traditional loop filer is replaced by UKF, the complexity increases which make the application a little difficult in hardware. In softeware receiver this algorithm need more caculation amount than the other two algorithms. Thus, wavelet denoising technique in PLL and adaptive bandwidth algorithm are more suitable for real-time and low complexity applications under high dynamic circumstance. Wavelet denoising technique in PLL is better without the knowledge of the dynamic and SNR,while adaptive bandwidth algorithm is better with the knowledge of the dynamic and SNR. In additon, these two algorithms are able to meet the requiremens of high dynamic signal tracking.