摘要
提出一种基于空域的网格特征匹配定位算法,利用信号衰减模型,将信号空间的匹配计算变换为距离空间的匹配计算,并计算相似度,选出最邻近的目标网格,最后通过加权计算进行精确求解.该方法有效降低非线性空间匹配带来的位置相似度误差,利用网格匹配算法的思想,进一步降低了定位误差,提高了定位精度,与基于信号强度的K近邻算法和基于信号强度的网格匹配算法相比,所提出的基于空域网格匹配算法降低了定位误差,定位精度提升近10%,满足了目前室内高精度定位需求.
A positioning algorithm based on grid-matching in space domain was proposed.By using the signal attenuation model,the matching calculation in signal domain was transformed into distance domain,and then the similarity rate was calculated.Therefore,the nearest object grid was detected.Finally,the accurate positioning result was obtained.The nonlinear spatial matching errors were reduced caused by the position of similarity.The positioning error was further reduced by learning grid matching method,which increased the positioning accuracy.Compared to RSSI-KNN（received signal strength indication-K nearest neighborhood）and RSSI-GRID algorithm,the proposed algorithm reduces the positioning error and the positioning accuracy by nearly 10%,which can meet the indoor positioning.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第3期19-22,共4页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家高技术研究发展计划资助项目(2012ΑΑ120801
2012ΑΑ120802)
关键词
室内定位
指纹定位
网格匹配
信号空间
空域
indoor location
fingerprint location
grid-matching
signal domain
distance domain
