Title :
Relaying Kalman filters for sensor networks
Author :
Liu, Zhigang ; Wang, Jinkuan ; Qu, Wei
Author_Institution :
Insitute of Eng. Optimization & Smart Antenna, Northeastern Univ., Qinhuangdao, China
Abstract :
Due to limited sensing range for sensors, moving object tracking has to be realized by relaying from one sensor to the other in sensor networks, and so the tracking procedure can be modelled as a Markov chain system. Based on the Bayesian theory, we propose the relaying Kalman filter(RKF) algorithm which introduce the equations of updating sensor probability, and reconstruct the innovation equation. Furthermore, the extension of the proposed method can be applied in nonlinear dynamic system. Finally, simulation results show the effectiveness of the proposed RKF algorithm.
Keywords :
Bayes methods; Kalman filters; Markov processes; ad hoc networks; wireless sensor networks; Bayesian theory; Markov chain system; relaying Kalman filter algorithm; sensor networks; Bayesian methods; Collaboration; Filtering theory; Intelligent sensors; Kalman filters; Nonlinear equations; Relays; Sensor systems; Technological innovation; Time measurement; Bayesian theory; Kalman filter; Markov chain; target tracking; wireless sensor networks;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541281
