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Data fusion of power and time measurements for mobile terminal location

机译:移动终端定位的功率和时间测量的数据融合

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The location of mobile terminals in cellular networks is an important problem with applications in resource allocation, location sensitive browsing, and emergency communications. Finding cost effective location estimation techniques that are robust to non-line of sight (NLOS) propagation, quantization, and measurement noise is a key problem in this area. Quantized time difference of arrival (TDoA) and received signal strength (RSS) measurements can be made simultaneously by CDMA cellular networks at low cost. The different sources of errors for each measurement type cause RSS and TDoA measurements to contain independent information about mobile terminal location. This paper applies data fusion to combine the information of RSS and TDoA measurements to calculate a superior location estimate. Nonparametric estimation methods, that are robust to variations of measurement noise and quantization, are employed to calculate the location estimates. It is shown how the data fusion location estimators are robust, provide lower error than the estimators based on the individual measurements, and have low implementation cost.
机译:蜂窝网络中移动终端的位置是资源分配,位置敏感浏览和紧急通信中的应用的重要问题。寻找对非视线(NLOS)传播,量化和测量噪声具有鲁棒性的经济有效的位置估计技术是该领域的关键问题。 CDMA蜂窝网络可以以低成本同时进行量化的到达时间差(TDoA)和接收信号强度(RSS)测量。每种测量类型的不同错误源导致RSS和TDoA测量包含有关移动终端位置的独立信息。本文应用数据融合来结合RSS和TDoA测量的信息,以计算出更好的位置估计。对测量噪声和量化变化具有鲁棒性的非参数估计方法用于计算位置估计。它显示了数据融合位置估计器的鲁棒性,比基于单独测量的估计器提供的误差低,实现成本低。

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