Probability-based clustering and its application to WLAN location estimation

Wireless local area networks (WLAN) localization based on received signal strength is becoming an important enabler of location based services. Limited efficiency and accuracy are disadvantages to the deterministic location estimation techniques. The probabilistic techniques show their good accuracy...

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Bibliographic Details
Published in:Shanghai jiao tong da xue xue bao 2008-10, Vol.13 (5), p.547-552
Main Authors: Zhang, Ming-hua, Zhang, Shen-sheng, Cao, Jian
Format: Article
Language:English
Subjects:
Architecture
Computer Science
Electrical Engineering
Engineering
Life Sciences
Materials Science
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Summary:Wireless local area networks (WLAN) localization based on received signal strength is becoming an important enabler of location based services. Limited efficiency and accuracy are disadvantages to the deterministic location estimation techniques. The probabilistic techniques show their good accuracy but cost more computation overhead. A Gaussian mixture model based on clustering technique was presented to improve location determination efficiency. The proposed clustering algorithm reduces the number of candidate locations from the whole area to a cluster. Within a cluster, an improved nearest neighbor algorithm was used to estimate user location using signal strength from more access points. Experiments show that the location estimation time is greatly decreased while high accuracy can still be achieved.
ISSN:1007-1172
1995-8188
DOI:10.1007/s12204-008-0547-0