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A Particle Filter Based Train Localization Scheme Using Wireless Sensor Networks

机译:使用无线传感器网络的基于粒子滤波的列车定位方案

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Real-time train localization is essential to ensure the safety of modern railway transportation. This paper investigates the feasibility to achieve real-time and accurate train localization using wireless sensor networks. We carry out on- site experiments in a railway environment and demonstrate that Received Signal Strength Indicator (RSSI) is a good estimator for train localization. By combining the advantages of RSSI-based distance estimation and particle filtering techniques, we design a particle filter based train localization scheme and propose a novel Weighted RSSI Likelihood Function (WRLF) for updating the weights of particles. The proposed scheme is evaluated through simulations using the data obtained from the on-site measurements. Simulation results demonstrate that our scheme can achieve high localization accuracy, and is robust to changes in train speed and the deployment density of anchor sensors.
机译:实时火车本地化对于确保现代铁路运输的安全至关重要。本文研究了使用无线传感器网络实现实时,准确的火车定位的可行性。我们在铁路环境中进行了现场实验,并证明了接收信号强度指示器(RSSI)是火车本地化的良好估算器。结合基于RSSI的距离估计和粒子滤波技术的优势,我们设计了一种基于粒子滤波的火车定位方案,并提出了一种新颖的加权RSSI似然函数(WRLF)来更新粒子的权重。通过使用从现场测量获得的数据进行仿真,对提出的方案进行了评估。仿真结果表明,该方案可以实现较高的定位精度,并且对列车速度和锚传感器的部署密度的变化具有鲁棒性。

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