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Because of the location failure of the global positioning system (GPS) in dense urban areas and indoor environments, a seamless positioning system based on GPS, Beidou, and digital television multimedia broadcasting (DTMB), which has nonlinear model characteristics, has been proposed. This paper focuses on the dynamic positioning tracking effect of two kinds of nonlinear filtering algorithm under the three-dimensional planar variable turn model (PVTM); that is, the nonlinear filtering algorithm mainly contains an extended Kalman filter (EKF) and a particle filter (PF). Our simulation has been carried out from two aspects; on one hand, the number of particles affects the position tracking precision in the PF algorithm. On the other hand, the location tracking effects of the PF and EKF algorithms have been comparatively analyzed using the same simulation model. Theoretical analysis and simulation results show that the filtering trajectories of EKF and PF are basically consistent with the real trajectory, but the tracking performance of the PF algorithm is higher than that of the EKF algorithm. Error means of 500 and 100 particles are 2.8736 and 5.3601 m, respectively. The error mean of EKF is 11.2065 m. The seamless positioning system can meet the positioning accuracy, coverage, and real-time performance requirements. The feasibility and superiority of the seamless positioning system have been proved. Such studies have positive practical and profound historically significant effects on the positioning system in the development of China’s independent intellectual property rights based on DTMB and Beidou signals.

Research on Dynamic Tracking of Seamless Positioning Based on Global Positioning System, Beidou, and Digital Television Multimedia Broadcasting