Device-free localization and tracking as an emerging technology has attracted substantial research attention in wireless sensor networks. However, there is much room for improvement in localization and tracking accuracy. In this paper, by using received signal strength (RSS) measurements we propose an enhanced geometric filter which consists of a series of weights corresponding to RSS, distance, and angle, respectively. Specifically, RSS-based weights are dependent on the change in RSS of communication links to remove improbable target locations. To ensure robust tracking performance, distance-based weights are assigned to probable target locations. Angle-based weights are used to ensure the correct direction of motion. Experimental results demonstrate that the proposed geometric filter could improve the accuracy of positioning by up to 50.8% for non-straight path and 48.3% for straight path over some state-of-the-art methods.

无设备定位和跟踪作为一项新兴技术在无线传感器网络中引起了广泛的研究关注。但是，定位和跟踪精度还有很大的提升空间。在本文中，通过使用接收信号强度 (RSS) 测量，我们提出了一种增强的几何滤波器，该滤波器由一系列分别对应于 RSS、距离和角度的权重组成。具体来说，基于 RSS 的权重取决于通信链路 RSS 的变化，以消除不可能的目标位置。为了确保稳健的跟踪性能，将基于距离的权重分配给可能的目标位置。基于角度的权重用于确保正确的运动方向。实验结果表明，所提出的几何滤波器可以将定位精度提高多达 50。