首页> 外文会议>International Conference on Pervasive Systems and Computing(PSC'05); 20050627-30; Las Vegas,NV(US) >Positioning and Tracking with NLOS Mitigation Using Extended Kalman Filter in UWB Systems
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Positioning and Tracking with NLOS Mitigation Using Extended Kalman Filter in UWB Systems

机译:在UWB系统中使用扩展卡尔曼滤波器进行NLOS缓解的定位和跟踪

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摘要

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.
机译:本文提出了一种用于超宽带(UWB)环境的,使用偏置扩展卡尔曼滤波器,具有NLOS误差减轻功能的定位和跟踪技术。 NLOS错误被认为是无线定位系统中的主要错误来源之一。为了在UWB定位系统中实现高精度的定位和跟踪,推导了适用于UWB系统的NLOS识别和缓解技术。卡尔曼滤波器(KF)和扩展卡尔曼滤波器(EKF)用于平滑距离数据,减轻NLOS误差并跟踪移动轨迹。提出了一种带有滑动窗口的方法来处理范围数据,以识别UWB系统中的NLOS / LOS条件。位置估计和跟踪的仿真结果表明,所提出的带有滑动数据窗口的技术能够提高NLOS / LOS识别中的检测概率。仿真还表明,带偏置扩展卡尔曼滤波器的NLOS缓解方法在位置估计方面的准确性最高,在定位和跟踪方面优于其他方法。

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