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R-Factor: A New Parameter to Enhance Location Accuracy in RSSI Based Real-time Location Systems

机译:R因子:基于RSSI的实时定位系统中提高定位精度的新参数

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The fundamental cause of localization error in an indoor environment is fading and spreading of the radio signals due to scattering, diffraction, and reflection. These effects are predominant in regions where there is no-line-of-sight (NLoS) between the transmitter and the receiver. Efficient algorithms are needed to identify the subset of receivers that provide better localization accuracy. This paper introduces a new parameter called the R-Factor to indicate the extent of radial distance estimation error introduced by a receiver and to select a subset of receivers that result in better accuracy in real-time location determination systems (RTLS). In addition, it was demonstrated that location accuracy improves with R-factor reduction. Further, it was shown that for a given R-factor threshold, localization accuracy is enhanced either by increasing the number of receivers that fall below this threshold or by increasing the diversity channel count with appropriate combining of signals from diversity. Therefore, existing localization algorithms can utilize R-factor and diversity through selection combining to improve accuracy. Both analytical and experimental results are included to justify the theoretical results in terms of improvement in accuracy by using R-factor.
机译:室内环境中定位误差的根本原因是由于散射,衍射和反射导致无线电信号衰减和扩散。在发射器和接收器之间没有视线(NLoS)的区域中,这些影响尤为明显。需要有效的算法来识别提供更好定位精度的接收机子集。本文引入了一个称为R因子的新参数,以指示接收器引入的径向距离估计误差的程度,并选择一个接收器子集,以提高实时定位系统(RTLS)的准确性。另外,已经证明,随着R因子的减小,定位精度提高。此外,已经表明,对于给定的R因子​​阈值,可以通过增加落入该阈值以下的接收器数量或通过适当地组合来自分集的信号来增加分集信道数来提高定位精度。因此,现有的定位算法可以通过选择结合利用R因子和分集来提高准确性。分析和实验结果都包括在内,以通过使用R因子提高精度来证明理论结果。

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