Performance analysis of a novel kalman filter-based signal tracking loop

Though the GNSS receiver baseband signal processing realizes more precise estimation by using Kalman Filter, traditional KF-based tracking loops estimate code phase and carrier frequency simultaneously by a single filter. In this case, the error of code phase estimate can affect the carrier frequency tracking loop, which is vulnerable than code tracking loop. This paper presents a tracking architecture based on dual filter. Filters can performing code locking and carrier tracking respectively, hence, the whole tracking loop ultimately avoid carrier tracking being subjected to code tracking errors. The control system is derived according to the mathematical expression of the Kalman system. Based on this model, the transfer function and equivalent noise bandwidth are derived in detail. As a result, the relationship between equivalent noise bandwidth and Kalman gain is presented. Owing to this relationship, the equivalent noise bandwidth for a well-designed tracking loop can adjust automatically with the change of environments. Finally, simulation and performance analysis for this novel architecture are presented. The simulation results show that dual Kalman filters can restrain phase noise more effectively than the loop filter of the classical GNSS tracking channel, therefore this whole system seems more suitable to working in harsh environments.