首页> 外文期刊>EURASIP journal on advances in signal processing >Nonparametric Bayesian Filtering for Location Estimation, Position Tracking, and Global Localization of Mobile Terminals in Outdoor Wireless Environments
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Nonparametric Bayesian Filtering for Location Estimation, Position Tracking, and Global Localization of Mobile Terminals in Outdoor Wireless Environments

机译:用于室外无线环境中移动终端的位置估计,位置跟踪和全局定位的非参数贝叶斯滤波

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摘要

The mobile terminal positioning problem is categorized into three different types according to the availability of (1) initial accurate location information and (2) motion measurement data.Location estimation refers to the mobile positioning problem when both the initial location and motion measurement data are not available. If both are available, the positioning problem is referred to as position tracking. When only motion measurements are available, the problem is known as global localization. These positioning problems were solved within the Bayesian filtering framework. Filter derivation and implementation algorithms are provided with emphasis on the mapping approach. The radio maps of the experimental area have been created by a 3D deterministic radio propagation tool with a grid resolution of 5?m. Real-world experimentation was conducted in a GSM network deployed in a semiurban environment in order to investigate the performance of the different positioning algorithms.
机译:根据(1)初始准确位置信息和(2)运动测量数据的可用性,将移动终端定位问题分为三种不同类型。位置估计是指当初始位置和运动测量数据均未同时存在时的移动定位问题可用。如果两者都可用,则定位问题称为位置跟踪。当仅运动测量可用时,该问题称为全局定位。这些定位问题是在贝叶斯过滤框架内解决的。提供了过滤器推导和实现算法,重点是映射方法。实验区域的无线电图是由3D确定性无线电传播工具创建的,其网格分辨率为5?m。为了研究不同定位算法的性能,在半郊区环境中部署的GSM网络中进行了实际实验。

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