基于多分布密度位置指纹的高效室内定位算法研究

摘要

To improve the prediction speed in indoor localization, a novel algorithm based on fingerprint with varied scales was proposed. It divided the region of interest into distinct zones with distinctive coverage indicators, and reference positions with different distribution density were set in the region. According the time relevance and strength vary of the RSS from the anchors, the grids-matching process was greatly sped up for the usage of coverage indictors and the features of the location fingerprint extracted with the PCA, which made the proposed method fit the demand of application with limited power and memory. Experimental results indicate that accuracy of the positioning is ensured with the reduced energy-consuming, and more flexible about the number of anchors and the grid distribution.%为提高定位效率,提出了一种基于多分布密度位置指纹、精度渐进的室内定位算法.该算法把定位区域分为多个局部区域,并设定不同分布密度的参考位置点,根据来自锚节点的接收信号强度(RSS)时间和强度分布,通过各局部区域对应的信号覆盖向量和主成分分析法(PCA)提取的稀疏指纹的特征实现层次化匹配,有效减少在线指纹匹配过程的计算量,有利于目标节点存储空间和能耗的优化.实验结果表明,提出的算法在定位精度上不逊于其他室内定位算法,并且对锚节点分布密度依赖度小.