This letter proposes a novel successive weighted received signal strength (RSS) indoor localization and tracking system that projects previous time instance estimated mobile device (MD) position to provide projected RSS values. Such RSS projection increases the number of available RSS from N_m to N_m + N_AP, where N_AP is the total number of access points and N_m is the number of RSS values measured by MD, ranging from 0 to N_AP. Our proposed system thus resolves the issues associated with insufficient or no RSS values received by MD. Inertial navigation system (INS) is merged with RSS localization system to provide a weighted fusion of projected and measured RSS values. The weighting factors are derived based on the INS and RSS localization accuracy where the former is initially accurate but deteriorates with time and the latter is time-independent but environment-dependent. The proposed system was tested in indoor environments and outperformed other existing localization systems such as RSS and INS fusion using extended Kalman filter and non-line-of-sight (NLOS) selection scheme, especially in heavy multipath environment, by 42% and 75%, respectively.

中文翻译：

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使用连续加权RSS投影的室内定位和跟踪系统

这封信提出了一种新颖的连续加权接收信号强度 (RSS) 室内定位和跟踪系统，该系统可以预测先前时间实例估计的移动设备 (MD) 位置以提供预测的 RSS 值。这种 RSS 投影增加了可用 RSS 的数量牛_米 至 牛_米 + N_AP , 其中N_AP是接入点的总数，牛_米 是 MD 测量的 RSS 值的数量，范围从 0 到 N_美联社。因此，我们提出的系统解决了与 MD 接收到的 RSS 值不足或没有相关联的问题。惯性导航系统 (INS) 与 RSS 定位系统相结合，以提供投影和测量 RSS 值的加权融合。权重因子是基于 INS 和 RSS 定位精度得出的，其中前者最初是准确的，但随着时间的推移而恶化，后者与时间无关但与环境有关。所提出的系统在室内环境中进行了测试，并在使用扩展卡尔曼滤波器和非视距 (NLOS) 选择方案的其他现有定位系统（例如 RSS 和 INS 融合）方面优于其他现有定位系统，尤其是在重度多径环境中，性能分别高出 42% 和 75% ， 分别。