摘要
针对基于接收信号强度指示(received signal strength indication,RSSI)测距定位受距离影响较大、室内环境下蓝牙信标信号不稳定等问题,文章提出一种基于贝叶斯定理的概率定位算法。该算法以测量蓝牙RSSI信息作为先验信息,通过设置距离阈值自适应筛选定位信标,基于信号分布概率符合高斯分布的特性,对多个定位信标分别利用贝叶斯算法估算待定点的位置分布概率,以概率之和最大值点作为待定点的估计位置。实验结果表明,静态定位时所提算法定位误差在1.5、2.0 m以内的概率分别为80%、95%,平均定位误差为1.04 m,动态定位时所提算法定位误差在3.0 m以内的概率为90%,平均定位误差为1.65 m;与传统加权质心定位算法相比,静、动态平均定位精度分别提高22.4%、21.8%,极大提高了室内复杂环境下蓝牙测距定位的稳定性和精度。
Aiming at the problems that the received signal strength indication(RSSI)ranging positioning is greatly affected by the distance and the beacon signal is unstable in indoor environments,this paper proposed a probabilistic localization algorithm based on Bayes’theorem.The algorithm used the measurement of Bluetooth RSSI as the prior information,and dynamically selected the positioning beacons by setting a distance threshold.Based on the characteristics of the signal distribution probability conforming to the Gaussian distribution,the Bayesian algorithm was used to estimate the position distribution probability of the pending points for multiple positioning beacons,and selected the coordinates of the maximum probability point as the estimated position of the unknown nodes.Experimental results showed that the probability of the proposed algorithm’positioning error within 1.5 m and 2.0 m in static positioning is 80%and 95%,respectively,and the average positioning error is 1.04 m.The probability of the proposed algorithm’s positioning error within 3.0 m in dynamic positioning is 90%,and the average positioning error is 1.65 m.Compared with the traditional weighted centroid positioning algorithm,the average accuracy is improved by 22.4%and 21.8%,respectively,which greatly improves the stability and accuracy of Bluetooth localization in complex indoor environment.
作者
刘奔
马昌忠
金俊超
靳赛州
李喜喜
LIU Ben;MA Changzhong;JIN Junchao;JIN Saizhou;LI Xixi(Key Laboratory of Land Environment and Disaster Monitoring of Ministry of Natural Resources, China University of Mining and Technology, Xuzhou 221116, China;School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;Guangzhou South Surveying and Mapping Technology Co., Ltd., Xi’an Branch, Xi’an 710054, China)
出处
《合肥工业大学学报（自然科学版）》
CAS
北大核心
2021年第10期1413-1419,共7页
Journal of Hefei University of Technology：Natural Science
基金
国家重点研发计划资助项目(2016YFB0502105)
国家自然科学基金资助项目(41371423)。
关键词
室内定位
测距定位
贝叶斯定理
概率算法
indoor positioning
ranging positioning
Bayes’theorem
probability algorithm
