基于时间反转的二阶段Wi-Fi室内定位方法

受Wi-Fi系统有限物理带宽限制,时间反转定位算法的定位精度难以得到提升。当定位范围较大时,在线定位阶段所需的匹配运算量更大,导致定位时间增长。针对上述问题,本文提出了一种基于时间反转的二阶段Wi-Fi室内定位方法。首先对接收信号强度和信道频率响应进行离线采集,利用接收信号强度和k近邻匹配算法进行位置粗估计,大致确定待测点所在范围。随后根据粗估计结果筛选原始指纹库,构建指纹库子集。在位置精估计阶段,计算待测点信道频率响应与指纹库子集中各参考点处信道频率响应的信号组合共振能量,通过最大值搜索寻找组合共振能量最大的参考点,将其坐标值作为位置估计结果。实验结果表明,所提算法相比于传统定位算法在精度和运行速度上有明显提升,在非直射环境下仍能保证较高的定位精度。

A Two-way Method of Wi-Fi Indoor Positioning based on Time-Reversal

The limited bandwidth of Wi-Fi system makes it difficult to increase the accuracy of time-reversal positioning algorithm. When the positioning area becomes larger, calculation cost of the matching algorithm becomes more complicated which means more execution time is needed as well as more hardware resources. To solve those problems, the paper proposed a two-way method of Wi-Fi indoor positioning based on time-reversal algorithm. Firstly, the received signal strength (RSS) and channel frequency response are collected. Then a rough estimation using RSS and k nearest neighbor algorithm is conducted to get an approximate location. Based on the rough estimation, the origin fingerprint database is filtered to construct a sub-database. In the accurate estimation phase, the combined time-reversal resonating strength (CTRRS) between the test point and each reference point in the sub-database is calculated. Finally, a maximum search procedure is utilized to find out the reference point with the largest CTRRS, and its known location is used as the positioning result. The experimental results show that compared with the existing positioning methods, the proposed method increases the accuracy and deduces the time cost. The positioning accuracy is acceptable even in non-line of sight environments.