DocumentCode
2768903
Title
Noise reduction for variance-based radio tomographic localization
Author
Zhao, Yang ; Patwari, Neal
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Utah, Salt Lake City, UT, USA
fYear
2011
fDate
27-30 June 2011
Firstpage
155
Lastpage
157
Abstract
We propose to demonstrate a new radio tomographic localization algorithm - subspace variance-based radio tomography (SubVRT), which is more robust to RSS variations caused by objects that are intrinsic parts of the environment. We first introduce the subspace decomposition method, then we derive the formulations of SubVRT, and finally we describe the demonstration setup, requirements and procedures.
Keywords
noise; radio direction-finding; tomography; wireless sensor networks; RF sensor network; noise reduction; subspace decomposition method; subspace variance-based radio tomography localization; Calibration; Fans; Humans; Motion measurement; Real time systems; Time measurement; Tomography;
fLanguage
English
Publisher
ieee
Conference_Titel
Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2011 8th Annual IEEE Communications Society Conference on
Conference_Location
Salt Lake City, UT
ISSN
2155-5486
Print_ISBN
978-1-4577-0094-1
Type
conf
DOI
10.1109/SAHCN.2011.5984889
Filename
5984889
Link To Document