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Mobile Location Estimation Using Fuzzy-Based IMM and Data Fusion

机译:基于模糊IMM和数据融合的移动位置估计

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The location of mobile station is an important issue for wireless communication systems. A location estimation scheme using fuzzy-based Interacting Multiple Model (IMM) smoother is proposed in this paper. It combines the time-of-arrival (TOA) and the received signal strength (RSS) measurements to achieve high location accuracy. The fuzzy technique is used to interpolate several linear equations to approximate the nonlinear RSS measurement. The IMM is employed as a switch between the line-of-sight (LOS) and non-line-of-sight (NLOS) states which are considered to be a Markov process with two interactive modes. By integrating the fuzzy filtering and the IMM method for range estimation between the corresponding base station (BS) and mobile station (MS), the proposed robust scheme, in association with data fusion, can efficiently mitigate the NLOS effects on the measurement range error. Simulation results are given to confirm the performance of the proposed method.
机译:移动站的位置对于无线通信系统是重要的问题。提出了一种基于模糊交互多模型平滑器的位置估计方案。它结合了到达时间(TOA)和接收信号强度(RSS)测量,以实现较高的定位精度。模糊技术用于对几个线性方程进行插值,以近似非线性RSS测量。 IMM被用作视线(LOS)状态和非视线(NLOS)状态之间的切换,这被认为是具有两种交互模式的马尔可夫过程。通过集成模糊滤波和用于相应基站(BS)与移动站(MS)之间距离估计的IMM方法,所提出的鲁棒方案与数据融合相关联,可以有效地减轻NLOS对测量范围误差的影响。仿真结果证明了该方法的有效性。

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