Positioning and tracking with NLOS mitigation using extended Kalman filter in UWB systems

In this paper, a positioning and tracking technique with NLOS error mitigation using biased extended Kalman filter for ultra-wideband (UWB) environments is presented. NLOS error is considered one of the major error sources in wireless location systems. To achieve high accuracy of positioning and tracking in UWB location systems, NLOS identification and mitigation techniques suitable for UWB systems are derived. Kalman filters (KFs) and extended Kalman filters (EKFs) are used for smoothing range data, mitigating NLOS errors and tracking mobile trajectory. A method with sliding window is proposed to process range data for identifying the NLOS/LOS condition in UWB systems. Simulation results of location estimation and tracking show that the proposed technique with sliding data window is capable of improving the probability of detection in NLOS/LOS identification. The simulations also show that the NLOS mitigation method with biased extended Kalman filter has the highest accuracy in location estimation, and outperforms other methods in positioning and tracking.