The four-point localization algorithm based on extended Kalman filter

In indoor environment positioning where GNSS signals are denied, the positioning accuracy of Ultra-Wideband (UWB) signals is often compromised due to Non-Line-of-Sight (NLOS) effects, resulting in degraded indoor localization performance. To address this issue, a four-point UWB localization algorithm based on the Extended Kalman Filter (EKF) is proposed. The algorithm is evaluated using error assessment metrics, and its effectiveness and applicability are verified. The EKF is employed to optimize trajectory estimation, providing an accurate trajectory model. Experimental results demonstrate that the proposed algorithm significantly improves the static and dynamic positioning accuracy of UWB in NLOS conditions.