基于改进级联滤波的UWB室内定位算法OA

The UWB indoor positioning is susceptible to non-line-of-sight(NLOS)error interference,which leads to reduced positioning accuracy,so this paper proposes a UWB indoor positioning algorithm based on an improved cascaded filtering technique.This algorithm employs a two-stage optimization framework to achieve error suppression and precise positioning.In the first stage,the improved Kalman filter(IKF)algorithm is used to correct errors in the original ranging values.The algorithm dynamically adjusts the Kalman gain by analyzing the symbols of the innovation sequence,so as to reduce the impact of NLOS errors on the ranging results.In the second stage,the improved particle filter(IPF)algorithm is used to solve the target position.Based on the traditional particle filter algorithm,residual analysis is introduced to dynamically adjust the weights of the particles,giving higher weights to high-likelihood particles.Meanwhile,a screening and elimination mechanism is introduced to remove low-weight particles,and the retained particles are finally used to solve the target position.Simulations demonstrate that the proposed algorithm significantly improves positioning accuracy and operational efficiency in indoor NLOS environments while exhibiting excellent robustness.To sum up,the proposed method can provide a certain level of technical support for indoor positioning.