DocumentCode
3310853
Title
Signal processing by particle filtering for binary sensor networks
Author
Djuric, Peter M. ; Vemula, Mahesh ; Bugallo, Monica F.
Author_Institution
Dept. of Electr. & Comput. Eng., Stony Brook Univ., NY, USA
fYear
2004
fDate
1-4 Aug. 2004
Firstpage
263
Lastpage
267
Abstract
In a wireless sensor network, limited power, communication, and computational resources are the major constraints that have to be overcome for their successful deployment and utilization. Binary sensor networks are a class of networks that get around these constraints. There, the sensors transmit only a binary digit on the occurrence of the event of interest, and therefore, the signals that reach the fusion center of these networks are highly compressed and pose challenging problems for recovering the sensed information. We consider the problem of tracking a vehicle, which moves along a 2-dimensional space, by using a binary sensor network that fuses information by particle filtering.
Keywords
Monte Carlo methods; nonlinear filters; sensor fusion; target tracking; wireless sensor networks; binary sensor networks; fusion center; nonlinear filters; particle filtering; sequential Monte Carlo methods; signal processing; target tracking; vehicle tracking; wireless sensor network; Computer networks; Fuses; Information filtering; Information filters; Intelligent sensors; Sensor fusion; Sensor phenomena and characterization; Signal processing; Target tracking; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Digital Signal Processing Workshop, 2004 and the 3rd IEEE Signal Processing Education Workshop. 2004 IEEE 11th
Print_ISBN
0-7803-8434-2
Type
conf
DOI
10.1109/DSPWS.2004.1437955
Filename
1437955
Link To Document