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)。...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。展开更多
The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when im...The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when immersed in complex backgrounds. To cope with this problem, we propose an effective infrared target detection algorithm based on temporal target detection and association strategy. First, a temporal target detection model is developed to segment the interested targets. This model contains mainly three stages, i.e., temporal filtering,temporal target fusion, and cross-product filtering. Then a graph matching model is presented to associate the targets obtained at different times. The association relies on the motion characteristics and appearance of targets,and the association operation is performed many times to form continuous trajectories which can be used to help disambiguate targets from false alarms caused by random noise or clutter. Experimental results show that the proposed method can detect slowly moving infrared targets in complex backgrounds accurately and robustly, and has superior detection performance in comparison with several recent methods.展开更多
文摘针对行人航位推算(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。
基金the National Natural Science Foundation of China(Nos.61273170 and 61503206)the Zhejiang Provincial Natural Science Foundation of China(Nos.LZ16F030002 and LZ15F030001)
文摘The special characteristics of slowly moving infrared targets, such as containing only a few pixels,shapeless edge, low signal-to-clutter ratio, and low speed, make their detection rather difficult, especially when immersed in complex backgrounds. To cope with this problem, we propose an effective infrared target detection algorithm based on temporal target detection and association strategy. First, a temporal target detection model is developed to segment the interested targets. This model contains mainly three stages, i.e., temporal filtering,temporal target fusion, and cross-product filtering. Then a graph matching model is presented to associate the targets obtained at different times. The association relies on the motion characteristics and appearance of targets,and the association operation is performed many times to form continuous trajectories which can be used to help disambiguate targets from false alarms caused by random noise or clutter. Experimental results show that the proposed method can detect slowly moving infrared targets in complex backgrounds accurately and robustly, and has superior detection performance in comparison with several recent methods.
