传感技术学报2024，Vol.37Issue(2)：224-233,10.DOI:10.3969/j.issn.1004-1699.2024.02.007
融合压缩感知的指纹信息密度凝聚定位算法
Fingerprint Information Density Aggregation Positioning Algorithm Based on Compressed Sensing
摘要
Abstract
Aiming at the problems of bulky fingerprint database,redundant information and monotonous data processing mechanism in traditional fingerprint positioning methods,a fingerprint information density aggregation positioning algorithm based on compressed sens-ing is proposed,which realizes the cross mapping of compressed sampling,signal recovery to fingerprint database construction and online positioning.The complementary gain of the two effectively improves the positioning ability of the system.The region fuzzy partition is completed by the spatial feature correction clustering algorithm,and the scene feature is adaptive and the regional edge mismatch RP is included.Comprehensive evaluation and selection of regional optimal AP subsets from effectiveness,discrimination and measurability are carried out to aggregate information density.For location matching,sparse Bayesian Learning algorithm is selected to weaken the in-fluence of fingerprint correlation,and information sequence is introduced to enhance the nearest neighbor RP weight.The experimental results show that the proposed scheme has a good effect on streamlining fingerprint information and can effectively condense the value information of fingerprint database.The positioning accuracy is significantly better than algorithms in this field.Compared with the tradi-tional positioning algorithm,it has certain advantages and has high potential and application value.关键词
室内定位/指纹定位/压缩感知/聚类/AP选择Key words
indoor positioning/fingerprint positioning/compressive sensing/clustering/AP selection分类
信息技术与安全科学引用本文复制引用
张阳,秦宁宁..融合压缩感知的指纹信息密度凝聚定位算法[J].传感技术学报,2024,37(2):224-233,10.基金项目
国家自然科学基金项目(Nos.61702228) （Nos.61702228）
江苏省自然基金项目(Nos.BK20170198) （Nos.BK20170198）
