Receiver Key Technical Analysis And Composition Of The Navigation Algorithm To Achieve

Global Positioning System (GPS) is a precise , new-generation ,satellite-based positioning system. It is worldwide, all-weather navigation and timing system. GPS system has become increasingly important to both military and civilian navigation . The research about satellite positioning system have advanced many years abroad. Besides GPS system of America, there are GLONASS system promoted by Russia and "Galileo" system promoted by Europe that are all nowadays hotspots. Especially, "Bei Dou" double-star system has primarily come into being and will be improved on its performance continuously. Despite these, GPS system is still the most perfect and has been used in many fields. Assuredly, it is worth researching GPS system in order to improve other navigation systems.A GPS receiver is the key for a user to access the system. With the different applications, the performances of receivers are diverse . However, acquisition and tracking of GPS satellite signals are the most fundamental . They are performed in digital baseband processor(DBP) where navigation data is demodulated and GPS measurement data are extracted. A digital delay-lock loop(DDLL) is to track the PRN code and a digital phase lock loop(DPLL) is to track carrier phase. Therefore, following contents are provided from chapter 2 to chapter 4: The relation among input GPS satellite signal parameters, noise, receiver loop parameters and GPS measurement data have been achieved by means of detailedly modeling and simulation for DDLL and DPLL's work process, meanwhile, extending the loop order for the research of high dynamic, utilizing MATLAB curves simulation and Simulink dynamic simulation. Performance analysis for software GPS receiver have implemented altogether . GPS system has become the important component of ITS. Because of the limitation of GPS system for urban circumstance, the integrated navigation system for GPS and other sensors (Dead-Reckoning system is discussed only in this paper) could achieve considerable accuracy and reliability. The research about it has very significant market application value. The core of the integrated navigation system lies in multi-sensors data fusion algorithm. Chapter 5 designs a kind of self-adaptive integrated Kalman filtering algorithm which are verified by computer simulations.