DocumentCode :
2444616
Title :
Collaborative sensing to improve information quality for target tracking in wireless sensor networks
Author :
Xiao, Wendong ; Tham, Chen Khong ; Das, Sajal K.
Author_Institution :
Inst. for Infocomm Res., Agency for Sci., Technol. & Res. A*Star, Singapore, Singapore
fYear :
2010
fDate :
March 29 2010-April 2 2010
Firstpage :
99
Lastpage :
104
Abstract :
Due to limited network resources for sensing, communication and computation, information quality (IQ) in a wireless sensor network (WSN) depends on the algorithms and protocols for managing such resources. In this paper, for target tracking application in WSNs consisting of active sensors (such as ultrasonic sensors) in which normally a sensor senses the environment actively by emitting energy and measuring the reflected energy, we present a novel collaborative sensing scheme to improve the IQ using joint sensing and adaptive sensor scheduling. With multiple sensors participating in a single sensing operation initiated by an emitting sensor, joint sensing can increase the sensing region of an individual emitting sensor and generate multiple sensor measurements simultaneously. By adaptive sensor scheduling, the emitting sensor for the next time step can be selected adaptively according to the predicted target location and the detection probability of the emitting sensor. Extended Kalman filter (EKF) is employed to estimate the target state (i.e., the target location and velocity) using sensor measurements and to predict the target location. A Monte Carlo method is presented to calculate the detection probability of an emitting sensor. It is demonstrated by simulation experiments that collaborative sensing can significantly improve the IQ, and hence the tracking accuracy, as compared to individual sensing.
Keywords :
Kalman filters; Monte Carlo methods; nonlinear filters; probability; protocols; scheduling; sensors; target tracking; wireless sensor networks; Monte Carlo method; active sensor; adaptive sensor scheduling; collaborative sensing; detection probability; emitting sensor; extended Kalman filter; information quality; joint sensing; network resources; protocol; sensing region; sensor measurement; target location; target tracking; ultrasonic sensor; wireless sensor network; Adaptive scheduling; Collaboration; Computer network management; Computer networks; Energy measurement; Quality management; Resource management; Target tracking; Wireless application protocol; Wireless sensor networks; Kalman filter; collaborative sensing; information quality; joint sensing; sensor scheduling; target tracking; wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Communications Workshops (PERCOM Workshops), 2010 8th IEEE International Conference on
Conference_Location :
Mannheim
Print_ISBN :
978-1-4244-6605-4
Electronic_ISBN :
978-1-4244-6606-1
Type :
conf
DOI :
10.1109/PERCOMW.2010.5470610
Filename :
5470610
Link To Document :
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