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 However, the signals significantly vary over time and the pre-obtained radio map (or prior knowledge) outdated in the localization phase, thus causing the localization accuracy decrease.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