摘要
随着室内无线终端与智能手机的快速发展,室内定位技术成为近几年的研究热点之一。本文研究了基于低功耗蓝牙(BLE)和行人航位推算(PDR)技术,利用扩展卡尔曼滤波(EKF)进行融合处理的室内定位方法。该方法包含3部分:①离线阶段利用蓝牙指纹快速采集方法建立指纹库,在线阶段利用加权K邻近算法进行指纹定位;②利用手机内置传感器准确估计航向角,并结合步态识别算法和步长估计算法推算行人位置;③利用EKF对两种定位结果进行融合,获取最优位置估计。试验结果表明,融合定位方法的平均定位精度为1.17 m,90%的概率定位精度达到2 m。
With the rapid development of indoor wireless terminals and smart phones,indoor positioning technology has become one of the research hotspots in recent years.A novel indoor positioning method by fusing bluetooth low energy(BLE)and pedestrian dead reckoning(PDR)with extended kalman filter(EKF)is discussed.It includes the following three parts:①establish the BLE fingerprint library using fingerprint fast acquisition method in the offline phase and compute the location using weighted K-nearest neighbor fingerprint positioning method in the online phase;②estimate the heading angle by fusing the sensors in the mobile phone and calculate pedestrian position conbined with gait recognition algorithm and step-length estimation algorithm;③fuse the two positioning results above with EKF to obtain the optimal position estimation.The experiment result shows that the average positioning error is down to 1.17 m and the positioning accuracy reaches 2 m with 90%probability.
作者
冯昆
何涛
汪云甲
FENG Kun;HE Tao;WANG Yunjia(Tianjin Institute of Surveying and Mapping,Tianjin 300381,China;China University of Mining and Technology,Xuzhou 221116,China)
出处
《测绘通报》
CSCD
北大核心
2019年第S2期6-10,37,共6页
Bulletin of Surveying and Mapping
关键词
室内定位
低功耗蓝牙
指纹定位
行人航位推算
扩展卡尔曼滤波
indoor positioning
bluetooth low energy
fingerprint localization
pedestrian dead reckoning
extended kalman filter
