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A Collaborative Location Model for Mobile Position Estimation

机译:移动位置估计的协同位置模型

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摘要

In cellular networks, Several TDOA (time difference of arrival) location algorithms can be applied to mobile position estimation, however, each algorithm has its own limitations and none of them is proved to be the most reliable one under different channel environments. In this paper Kleine-Ostmann's data fusion model [1] is modified and a collaborative location model which incorporate position estimate of two major TDOA location algorithms is proposed. It is shown by analysis and simulation that more reliable and accurate estimated mobile position can be achieved based on this model.
机译:在蜂窝网络中,可以将几种TDOA(到达时间差)定位算法应用于移动位置估计,但是,每种算法都有其自身的局限性,没有一种被证明是在不同信道环境下最可靠的一种。本文对Kleine-Ostmann的数据融合模型[1]进行了修改,并提出了一种结合了两种主要TDOA定位算法的位置估计的协同定位模型。通过分析和仿真表明,基于该模型可以实现更可靠,更准确的估计移动位置。

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