Wang Zhenghuan, Liu Heng, Xu Shengxin, Bu Xiangyuan, An Jianping
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China.
Sensors (Basel). 2017 Apr 27;17(5):969. doi: 10.3390/s17050969.
Received-signal-strength-based (RSS-based) device-free localization (DFL) is a promising technique since it is able to localize the person without attaching any electronic device. This technology requires measuring the RSS of all links in the network constituted by several radio frequency (RF) sensors. It is an energy-intensive task, especially when the RF sensors work in traditional work mode, in which the sensors directly send raw RSS measurements of all links to a base station (BS). The traditional work mode is unfavorable for the power constrained RF sensors because the amount of data delivery increases dramatically as the number of sensors grows. In this paper, we propose a binary work mode in which RF sensors send the link states instead of raw RSS measurements to the BS, which remarkably reduces the amount of data delivery. Moreover, we develop two localization methods for the binary work mode which corresponds to stationary and moving target, respectively. The first localization method is formulated based on grid-based maximum likelihood (GML), which is able to achieve global optimum with low online computational complexity. The second localization method, however, uses particle filter (PF) to track the target when constant snapshots of link stats are available. Real experiments in two different kinds of environments were conducted to evaluate the proposed methods. Experimental results show that the localization and tracking performance under the binary work mode is comparable to the those in traditional work mode while the energy efficiency improves considerably.
基于接收信号强度（RSS）的无设备定位（DFL）是一项很有前景的技术，因为它能够在不附着任何电子设备的情况下对人员进行定位。该技术需要测量由多个射频（RF）传感器构成的网络中所有链路的RSS。这是一项能耗密集型任务，尤其是当RF传感器以传统工作模式工作时，在这种模式下，传感器直接将所有链路的原始RSS测量值发送到基站（BS）。传统工作模式对功率受限的RF传感器不利，因为随着传感器数量的增加，数据传输量会急剧增加。在本文中，我们提出了一种二进制工作模式，其中RF传感器向BS发送链路状态而不是原始RSS测量值，这显著减少了数据传输量。此外，我们针对二进制工作模式开发了两种定位方法，分别对应于静止和移动目标。第一种定位方法基于基于网格的最大似然（GML）制定，能够以较低的在线计算复杂度实现全局最优。然而，第二种定位方法在有链路状态的恒定快照时使用粒子滤波器（PF）来跟踪目标。我们在两种不同的环境中进行了实际实验，以评估所提出的方法。实验结果表明，二进制工作模式下的定位和跟踪性能与传统工作模式相当，同时能源效率有了显著提高。
