Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation

Shuopeng Wang, Peng Yang, Hao Sun
2018 Applied Sciences  
Fingerprinting acoustic localization usually requires tremendous time and effort for database construction in sampling phase and reference points (RPs) matching in positioning phase. To improve the efficiency of this acoustic localization process, an iterative interpolation method is proposed to reduce the initial RPs needed for the required positioning accuracy by generating virtual RPs in positioning phase. Meanwhile, a two-stage matching method based on cluster analysis is proposed for
more » ... ation reduction of RPs matching. Results reported show that, on the premise of ensuring positioning accuracy, two-stage matching method based on feature clustering partition can reduce the average RPs matching amount to 30.14% of the global linear matching method taken. Meanwhile, the iterative interpolation method can guarantee the positioning accuracy with only 27.77% initial RPs of the traditional method needed.
doi:10.3390/app8101862 fatcat:a6kri5seunhlbfnrncg4kz4as4