Title :
Node localization during power adjustment in wireless sensor networks
Author :
Ren, Hongliang ; Meng, Max Q H
Author_Institution :
Dept. of Biomed. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
Node localization is a challenging problem in wireless sensor networks, especially in the scenarios of tuning multiple transmit-powers. In this article, we utilized particle filter to infer static node position from the correlations between radio frequency (RF) received signal strength indication (RSSI) and distance under multiple power settings. The RSSI based stochastic measurement model was analyzed and followed by the particle filter design. The simulation results verified the performance of proposed algorithm for localization. The proposed method is contributive in terms of making advantages of multiple transmit power for localization.
Keywords :
particle filtering (numerical methods); radio direction-finding; stochastic processes; wireless sensor networks; multiple transmit-power tuning; node localization; particle filter design; power adjustment; radio frequency received signal strength indication; stochastic measurement model; wireless sensor network; Filtering; Kalman filters; Particle filters; Particle measurements; Power measurement; Probability distribution; Radio frequency; Runtime; State estimation; Wireless sensor networks;
Conference_Titel :
Robotics and Automation, 2009. ICRA '09. IEEE International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4244-2788-8
Electronic_ISBN :
1050-4729
DOI :
10.1109/ROBOT.2009.5152412