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中文摘要：
针对传统位置指纹图中的邻近参考点（ARP）信息未能得到较好利用的问题,提出一种在离线训练阶段建立基于接收信号强度（RSS）的位置指纹库和参考点（RP）物理邻近信息库的方法.通过利用待定位点与其所对应的最近邻参考点及参考点之间的物理邻近关系,来提高指纹概率定位方法的定位精度,即：在在线定位阶段,首先根据基于信号强度概率分布的贝叶斯算法计算得到待定位点的最近邻点;然后在物理邻近信息库中搜索最近邻点的物理邻近点,并在该最近邻和物理邻近点集合中,选取特征点集合用于贝叶斯二次估计;最后将具有最大后验（MAP）概率的特征点组的均值位置作为待定位点的估计位置.实验结果表明,与传统的无物理邻近数据库的指纹概率定位方法相比,在3m内的定位精度提高了约10％,有效提高了定位的可靠性.
英文摘要：
In order to make full use of Adjacent Reference Point （ARP） information in radio-map, a new method of establishing both location fingerprint database based on Received Signal Strength （RSS） and physical neighbor information database for each Reference Point （RP） in the off-line phase was proposed to improve the accuracy of fingerprinting-based probabilistic localization, hi the on-line phase, based on the probability distribution of RSS, the system first used Bayesian inference to calculate the most adjacent points for each test point. Then, by using physical neighbor information database, the system found the physical adjacent points with respect to the most adjacent points. In the set of most adjacent and physical adjacent points, the system selected feature points for second Bayesian inference. Finally, the system estimated the position of each test point at the center of the group of feature points which had the Maximum A Posterior （MAP） probability. The simulation results show that, compared with the traditional method without physical neighbor information database, the proposed method can improve the localization accuracy by nearly 10%, which enhances the reliability of location determination.
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