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
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;
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
Print_ISBN :
978-1-4577-0094-1
DOI :
10.1109/SAHCN.2011.5984889
