DocumentCode :
3546632
Title :
Research and improvement on indoor localization based on RSSI fingerprint database and K-nearest neighbor points
Author :
Zhang Guowei ; Xu Zhan ; Liu Dan
Author_Institution :
Res. Inst. Electron. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Volume :
2
fYear :
2013
fDate :
15-17 Nov. 2013
Firstpage :
68
Lastpage :
71
Abstract :
Aiming at the shortcomings of K nearest neighbor algorithm, this paper put forward an indoor location algorithm based on K nearest neighbor collection of reference points. The new algorithm in this paper expand the single relationship between test points and reference points to net relationship between test points and reference points and between test points´ close neighbor points and other reference points. The new algorithm uses the deeper information, and effectively reduces the influence of noise points. The new algorithm optimizes the formula of coordinate estimation through the occurrences of reference point. Experiments show that compared with K nearest neighbor localization algorithm, the new algorithm has improved on the positioning accuracy and stability.
Keywords :
data mining; direction-of-arrival estimation; indoor radio; K nearest neighbor points; RSSI fingerprint database; coordinate estimation; indoor localization; reference points; test points; Accuracy; Algorithm design and analysis; Databases; Euclidean distance; Fingerprint recognition; Indoor environments; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Circuits and Systems (ICCCAS), 2013 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-3050-0
Type :
conf
DOI :
10.1109/ICCCAS.2013.6765288
Filename :
6765288
Link To Document :
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