Title :
Improved particle filter algorithms for target tracking in binary wireless sensor network
Author :
Yang Xiaodong ; Xiang Fenghong ; Mao Jianlin ; Guo Ning
Author_Institution :
Fac. of Inf. Eng. & Autom., Kunming Univ. of Sci. & Technol., Kunming, China
Abstract :
Particle filter algorithm with adaptive process noise variance is proposed for target tracking applications in binary wireless sensor network (BWSN). The algorithm adopts updated variance of system noise to eliminate the cumulative effect of particle filter prediction error. It has better tracking accuracy when target travel with constant velocity or variable velocity. The simulation results show that the algorithm is superior to the standard particle filter.
Keywords :
particle filtering (numerical methods); target tracking; wireless sensor networks; adaptive process noise variance; binary wireless sensor network; constant velocity; cumulative effect; particle filter; prediction error; target tracking; target travel; variable velocity; IP networks; Particle filters; Prediction algorithms; Sensors; Target tracking; Wireless sensor networks; Adaptive-variance; Particle Filter; Target Tracking; Wireless Sensor Networks;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768