DocumentCode :
169057
Title :
Poster abstract: EIL — An environment-independent Device-free Passive Localization approach
Author :
Liqiong Chang ; Dingyi Fang ; Zhe Yang ; Xiaojiang Chen ; Ju Wang ; Weike Nie ; Tianzhang Xing
Author_Institution :
Sch. of Inf. Sci. & Technol., Northwest Univ., Xi´an, China
fYear :
2014
fDate :
15-17 April 2014
Firstpage :
291
Lastpage :
292
Abstract :
Most previous Device-free Passive Localization (DFL) methods are learning based and they assume the distribution of Received Radio Signal (RSS) distorted by an object is fixed across time. However, the signals significantly vary over time and the pre-obtained radio map (or prior knowledge) outdated in the localization phase, thus causing the localization accuracy decrease. To cope with this problem, this poster proposes, EIL, an environment-independent DFL approach which can improve the system robustness and localization accuracy by eliminating the interference of environment on RSS over time in both the training phase and the localization phase. Through both the extensive experiments and simulations, EIL keeps a range of 0.5m to 0.6m localization errors for 90% locations over time.
Keywords :
interference suppression; radionavigation; DFL methods; EIL; RSS; environment-independent device-free passive localization approach; interference elimination; localization phase; radio map; received radio signal; training phase; Accuracy; Distortion measurement; Educational institutions; Optical character recognition software; Robustness; Time measurement; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Processing in Sensor Networks, IPSN-14 Proceedings of the 13th International Symposium on
Conference_Location :
Berlin
Print_ISBN :
978-1-4799-3146-0
Type :
conf
DOI :
10.1109/IPSN.2014.6846768
Filename :
6846768
Link To Document :
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