针对行人航位推算(Pedestrian Dead Reckoning,PDR)室内定位系统的累计误差问题,提出了一种多维信息感知地标匹配的PDR定位算法(PDR positioning algorithm based Multi-imensional Information Perception Landmark Matching,MIPLM).算法利用行人在室内走廊环境下的众包轨迹,并基于突出性路口结构,从位置、航向、影响范围以及WiFi特征指纹等方面构建多维信息感知地标库.给出的自适应地标检测算法,结合航向约束轨迹相似度匹配模型,更新行人位置和航向,避免了本地化匹配过程对空间位置的强依赖性.实验结果表明,相比于其他地标构建及匹配算法,所提算法更好地反映了行人活动与室内空间结构的相关性,且在未知起始位置时,算法能够快速收敛并提供较高的定位精度,对于室内行人连续定位具有较高的应用价值.
PDR Positioning Algorithm Based Multi-Dimensional Information Perception Landmark Matching
Targeting at the cumulative error problem of pedestrian dead reckoning(PDR)indoor positioning system,a PDR positioning algorithm based multi-dimensional information perception landmark matching(MIPLM)is proposed.Based on the crowdsourced tracks of pedestrians in the indoor corridor environment and the prominent intersection structure,the multi-dimensional information perception landmark database is constructed from the aspects of location,heading,influence area and WiFi feature fingerprint.The proposed adap-tive landmark detection algorithm,combined with the trajectory similarity model of heading constraint,updates the pedestrian position and heading,which avoids the strong dependence on spatial position in the localization matching process.The experimental results show that,compared with other landmark construction and matching algorithms,the proposed algorithm can better reflect the correlation between pedestrian activity and indoor spatial structure.Moreover,when the initial location is unknown,the proposed algorithm can rapidly converge and provide higher positioning accuracy,which has a higher application value for the continuous positioning of indoor pedestrians.
indoor localizationpedestrian dead reckoningmulti-dimensional information perceptionlandmark matchingtrajectory similarity
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