一种关于地标辅助行人航位推算技术的改进室内定位方法
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摘要
近年来,基于智能手机的行人航位推算技术(pedestrian dead reckoning,PDR)、Wi-Fi以及多种融合室内定位技术得到了较快发展;与此同时,其存在对定位环境要求较高、定位结果偏差较大等缺点。为解决这一问题,在传统PDR基础上提出了一种结合地标库匹配的改进室内定位方法——地标辅助PDR定位算法(landmark-aided PDR algorithm,La PDR)。首先,将在传感器实时数据上识别出的特定地理位置(如墙、门、拐角、Wi-Fi接入点等)当作地标;然后,针对实验环境建立相应的地标库,目的是纠正传统PDR定位算法由于传感器安装精度较低及定位时间过长而产生的漂移。实验结果表明与传统PDR相比,地标辅助PDR定位精度明显提高,系统定位误差基本控制在1. 5 m以内。
In recent years,pedestrian dead reckoning( PDR),Wi-Fi and many fusion indoor positioning technologies based on smartphones have been developed greatly. At the same time,the existing methods also have disadvantages that can't be ignored,such as higher requirements on the positioning environment and larger positioning errors have been found. For this issue,an improved indoor location method based on traditional PDR is proposed,which is called landmark-aided PDR algorithm( LaPDR). First of all,the specific geographical locations( e. g.,wall,door,corner,Wi-Fi access point,etc.) that can be identified in the sensor data are used as landmark and corresponding landmark database is built for the experimental environment. This method can correct the drift of traditional PDR due to the sensor installation accuracy and long-term positioning. The experimental results show that the landmark-assisted PDR positioning effect is greatly improved compared with the traditional PDR,and the whole system positioning error is within 1. 5 m.
In recent years,pedestrian dead reckoning( PDR),Wi-Fi and many fusion indoor positioning technologies based on smartphones have been developed greatly. At the same time,the existing methods also have disadvantages that can't be ignored,such as higher requirements on the positioning environment and larger positioning errors have been found. For this issue,an improved indoor location method based on traditional PDR is proposed,which is called landmark-aided PDR algorithm( LaPDR). First of all,the specific geographical locations( e. g.,wall,door,corner,Wi-Fi access point,etc.) that can be identified in the sensor data are used as landmark and corresponding landmark database is built for the experimental environment. This method can correct the drift of traditional PDR due to the sensor installation accuracy and long-term positioning. The experimental results show that the landmark-assisted PDR positioning effect is greatly improved compared with the traditional PDR,and the whole system positioning error is within 1. 5 m.
引文
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2邹亮,潘州.基于2.4 GHz与5 GHz信号的Wi Fi指纹定位算法研究[J].科学技术与工程,2015,15(3):280-284Zou Liang,Pan Zhou.Study on Wi Fi fingerprint localization algorithm based on 2.4 GHz and 5 GHz signal[J].Science Technology and Engineering,2015,15(3):280-284
3金纯,马金辉,方天恩,等.基于时空相似模型的蓝牙室内定位RSSI指纹插值方法[J].科学技术与工程,2016,16(28):264-268Jin Chun,Ma Jinhui,Fang Tianen,et al.A method of RSSI fingerprint interpolation based on spatial-temporal similarity model for bluetooth[J].Science Technology and Engineering,2016,16(28):264-268
4张令文,杨刚.超宽带室内定位关键技术[J].数据采集与处理,2013,28(6):706-713Zhang Lingwen,Yang Gang.Ultra-wide-band based indoor positioning technologies[J].Journal of Data Acquisition&Processing,2013,28(6):706-713
5何海平,郭杭,方爽.基于模糊聚类的Zig Bee室内定位系统设计[J].电子技术应用,2016,42(5):72-73,77He Haiping,Guo Hang,Fang Shuang.Research of Zig Bee indoor positioning system based on the fuzzy clustering[J].Application of Electronic Technique,2016,42(5):72-73,77
6陈锐志,陈亮.基于智能手机的室内定位技术的发展现状和挑战[J].测绘学报,2017,46(10):1316-1326Chen Ruizhi,Chen Liang.Indoor positioning with smartphones:The state-of-the-art and the challenges[J].Acta Geodaetica et Cartographica Sinica,2017,46(10):1316-1326
7申崇江,冯成涛,崔莹,等.穿戴式室内行人航位推算系统研究[C]//五届中国卫星导航学术年会论文集---S9组合导航与导航新方法.北京:中国卫星导航学术年会组委会,2014:5Shen Chongjiang,Feng Chengtao,Cui Ying,et al.Research on wearable indoor pedestrian dead reckoning system[C]//The Proceedings of 5th China Satellite Navigation Conference-S9 Integrated Navigation and Navigation Method.Beijing:China Satellite Navigation Conference Organizing Committee,2014:5
8 Yuan Z,Lan H Y,Li Y,et al.PDR/INS/Wi Fi integration based on handheld devices for indoor pedestrian navigation[J].Micromachines2015,6(6):793-812
9 Sun Y C,Wang B.Indoor corner recognition from crowdsourced trajectories using smartphone sensors[J].Expert Systems with Applications,2017,82:266-277
10郭霖.第一行代码Android[M].北京:人民邮电出版社,2016:196-243Guo Lin.The first line of code Android[M].Beijing:Posts&Telecom Press,2016:196-243
11刘春燕.基于多源信息融合的行人航位推算室内定位方法[J].中国惯性技术学报,2016,24(2):208-214Liu Chunyan.Indoor localization method based on pedestrian dead reckoning aided by multi-source fusion[J].Journal of Chinese Inertial Technology,2016,24(2):208-214
12王励扬,翟昆朋,何文涛,等.四阶龙格库塔算法在捷联惯性导航中的应用[J].计算机仿真,2014,31(11):56-59Wang Liyang,Zhai Kunpeng,He Wentao,et al.Application of fourth-order Runge-Kutta algorithm in SINS[J].Computer Simulation,2014,31(11):56-59
13刘雷,慕艳艳,刘睿鑫.基于三轴加速度传感器的步长估算模型研究[J].传感器与微系统,2017,36(8):22-24,28Liu Lei,Mu Yanyan,Liu Ruixin.Research on model for step length estimating based on tri-axis acceleration sensor[J].Transducer and Microsystem Technologies,2017,36(8):22-24,28