فیلتر کالمن تطبیقی جدیدی مبتنی بر الگوریتم NLOS کاهش خطا

In this paper, we presented an algorithm for NLOS error mitigation based on adaptive Kalman filter with colored measurement noise. To eliminate NLOS error which induced by TOF-based distance measurements, a colored noise model is firstly established according to measurement noise and the filter parameters are adjusted dynamically based on the severity of NLOS environment. Then combined with adaptive Kalman filtering algorithm, the NLOS error mitigation process is adjusted in real time in order to obtain optimal estimation. The simulation experiments show that the algorithm has small error and high precision and is suitable for real-time dynamic location systems.