基于时间反转的二阶段Wi-Fi室内定位方法
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摘要
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,导致定位时间更长。针对上述问题,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。
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 sources. To solve those problems,this paper proposed a two-way method of Wi-Fi indoor positioning based on time-reversal algorithm. Firstly,it collected the received signal strength(RSS)and channel frequency response. Then it conducted a rough estimation using RSS and K nearest neighbor algorithm to get an approximate location. Based on the rough estimation,it filtered the origin fingerprint database to construct a sub-database. In the accurate estimation phase,it calculated the combined time-reversal resonating strength(CTRRS) between the test point and each reference point in the sub-database. Finally,it used a maximum search procedure to find out the reference point with the largest CTRRS,and regarded its known location 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.
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 sources. To solve those problems,this paper proposed a two-way method of Wi-Fi indoor positioning based on time-reversal algorithm. Firstly,it collected the received signal strength(RSS)and channel frequency response. Then it conducted a rough estimation using RSS and K nearest neighbor algorithm to get an approximate location. Based on the rough estimation,it filtered the origin fingerprint database to construct a sub-database. In the accurate estimation phase,it calculated the combined time-reversal resonating strength(CTRRS) between the test point and each reference point in the sub-database. Finally,it used a maximum search procedure to find out the reference point with the largest CTRRS,and regarded its known location 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.
引文
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[15]Xie Yaxiong,Li Zhenjiang,Li Mo.Precise power delay profiling with commodity Wi Fi[C]//Proc of International Conference on Mobile Computing and Networking.New York:ACM Press,2015:53-64.
[2]袁弋非,王欣晖,赵孝武.5G部署场景和潜在技术[J].电信网技术,2015(5):21-27.
[3]Gu Yanying,Lo A,Niemegeers I.A survey of indoor positioning systems for wireless personal networks[J].IEEE Communications Surveys&Tutorials,2009,11(1):13-32.
[4]席瑞,李玉军,侯孟书.室内定位方法综述[J].计算机科学,2016,43(4):1-6,32.
[5]He Suining,Chan S H G.Wi-Fi fingerprint-based indoor positioning:recent advances and comparisons[J].IEEE Communications Surveys&Tutorials,2016,18(1):466-490.
[6]Jin Yunye,Soh W S,Wong W C.Indoor localization with channel impulse response based fingerprint and nonparametric regression[J].IEEE Trans on Wireless Communications,2010,9(3):1120-1127.
[7]Venkatesh S,Buehrer R M.Non-line-of-sight identification in ultrawideband systems based on received signal statistics[J].IET Microwaves,Antennas&Propagation,2007,1(6):1120-1130.
[8]Chen Yan,Han Feng,Yang Yuhan,et al.Time-reversal wireless paradigm for green Internet of things:an overview[J].IEEE Internet of Things Journal,2014,1(1):81-98.
[9]Lerosey G,De R J,Tourin A,et al.Time reversal of electromagnetic waves[J].Physical Review Letters,2004,92(19):193904.
[10]Wu Z H,Han Yi,Chen Yan,et al.A time-reversal paradigm for indoor positioning system[J].IEEE Trans on Vehicular Technology,2015,64(4):1331-1339.
[11]Chen Chen,Chen Yan,Lai H Q,et al.High accuracy indoor localization:a Wi Fi-based approach[C]//Proc of IEEE International Conference on Acoustics,Speech and Signal Processing.Piscataway,NJ:IEEE Press,2016:6245-6249.
[12]Chen Chen,Chen Yan,Han Yi,et al.Achieving centimeter accuracy indoor localization on Wi Fi platforms:a frequency hopping approach[J].IEEE Internet of Things Journal,2017,4(1):122-134.
[13]Perahia E,Stacey R.Next generation wireless LANs:802.11n and802.11ac[M].London:Cambridge University Press,2013.
[14]O'hara B,Petrick A.IEEE 802.11 handbook:a designer’s companion[M].[S.l.]:IEEE Standards Association,2005.
[15]Xie Yaxiong,Li Zhenjiang,Li Mo.Precise power delay profiling with commodity Wi Fi[C]//Proc of International Conference on Mobile Computing and Networking.New York:ACM Press,2015:53-64.