电子学报2012，Vol.40Issue(9)：1876-1879,4.DOI:10.3969/j.issn.0372-2112.2012.09.027
基于BP神经网络和泰勒级数的室内定位算法研究
Research on Indoor Location Technology Based on Back Propagation Neural Network and Taylor Series
摘要
Abstract
Based on lots of research and analysis on indoor radio signal propagation features and the traditional indoor location algorithms,a new method that uses BP(Back Propagation) neural network to fit the indoor radio signal propagation model is proposed, which avoids inaccurately estimating the parameters A and n in the indoor radio signal propagation model. Distance value proportional to the RSSI(Received Signal Strength Indicator) input through the well-trained BP neural network is obtained, and then Taylor series expansion algorithm is used to determine the coordinates of the blind node.Finally,the simulation and experiment results on the ZigBee platform verify the feasibility and effectiveness of the proposed algorithm.关键词
室内定位/BP神经网络/RSSI(Received Signal Strength Indicator)/ZigBee/泰勒级数Key words
indoor location/back propagation neural network/received signal strength indicator/ZigBee/Taylor series分类
信息技术与安全科学引用本文复制引用
张会清,石晓伟,邓贵华,高学金,任明荣..基于BP神经网络和泰勒级数的室内定位算法研究[J].电子学报,2012,40(9):1876-1879,4.基金项目
国家科技重大专项(No.2009ZX05039-003) （No.2009ZX05039-003）
