UWB(Ultra-wideband)信号时间分辨率高、测距精度高。考虑到位置指纹定位法在复杂的室内环境中可以有效提供目标位置估计,因此将UWB测距值作为指纹信息,研究基于TOA(time of arrival)的UWB位置指纹定位法,指纹匹配算法选择加权K最近邻(w...UWB(Ultra-wideband)信号时间分辨率高、测距精度高。考虑到位置指纹定位法在复杂的室内环境中可以有效提供目标位置估计,因此将UWB测距值作为指纹信息,研究基于TOA(time of arrival)的UWB位置指纹定位法,指纹匹配算法选择加权K最近邻(weighted K nearest neighbors,WKNN)算法。仿真结果表明,WKNN算法采用卡方距离作为距离度量方式优于欧氏距离、曼哈顿距离和切比雪夫距离。WKNN算法中K值的大小对定位精度有着很大的影响,K值过大或过小,均会使定位精度降低;且K值的选择与指纹密度有关。展开更多
To position personnel in mines, the study discussed in this paper built on the tunnel personnel positioning method on the basis of both TOA and location-finger print(LFP) positioning. Given non-line of sight(NLOS) tim...To position personnel in mines, the study discussed in this paper built on the tunnel personnel positioning method on the basis of both TOA and location-finger print(LFP) positioning. Given non-line of sight(NLOS) time delay in signal transmission caused by facilities and equipment shielding in tunnels and TOA measurement errors in both LFP database data and real-time data, this paper puts forth a database data de-noising algorithm based on distance threshold limitation and modified mean filtering(MMF), as well as a real-time data suppression algorithm based on speed threshold limitation and MMF.On this basis, a nearest neighboring data matching algorithm based on historical location and the speed threshold limitation is used to estimate personnel location and realize accurate personnel positioning.The results from both simulation and the experiment suggest that: compared with the basic LFP positioning method and the method that only suppresses real-time data error, the tunnel personnel positioning methods based on TOA and modified LFP positioning permits effectively eliminating error in TOA measurement, making the measured data close to the true positional data, and dropping the positioning error:the maximal positioning error in measurements from experiment drops by 9 and 3 m, respectively, and the positioning accuracy of 3 m is achievable in the condition used in the experiment.展开更多
文摘UWB(Ultra-wideband)信号时间分辨率高、测距精度高。考虑到位置指纹定位法在复杂的室内环境中可以有效提供目标位置估计,因此将UWB测距值作为指纹信息,研究基于TOA(time of arrival)的UWB位置指纹定位法,指纹匹配算法选择加权K最近邻(weighted K nearest neighbors,WKNN)算法。仿真结果表明,WKNN算法采用卡方距离作为距离度量方式优于欧氏距离、曼哈顿距离和切比雪夫距离。WKNN算法中K值的大小对定位精度有着很大的影响,K值过大或过小,均会使定位精度降低;且K值的选择与指纹密度有关。
基金Project supports from the National Science Foundation of China(No.51134024)the National High Technology Research and development Program of China(No.2012AA062203)are acknowledged
文摘To position personnel in mines, the study discussed in this paper built on the tunnel personnel positioning method on the basis of both TOA and location-finger print(LFP) positioning. Given non-line of sight(NLOS) time delay in signal transmission caused by facilities and equipment shielding in tunnels and TOA measurement errors in both LFP database data and real-time data, this paper puts forth a database data de-noising algorithm based on distance threshold limitation and modified mean filtering(MMF), as well as a real-time data suppression algorithm based on speed threshold limitation and MMF.On this basis, a nearest neighboring data matching algorithm based on historical location and the speed threshold limitation is used to estimate personnel location and realize accurate personnel positioning.The results from both simulation and the experiment suggest that: compared with the basic LFP positioning method and the method that only suppresses real-time data error, the tunnel personnel positioning methods based on TOA and modified LFP positioning permits effectively eliminating error in TOA measurement, making the measured data close to the true positional data, and dropping the positioning error:the maximal positioning error in measurements from experiment drops by 9 and 3 m, respectively, and the positioning accuracy of 3 m is achievable in the condition used in the experiment.
