شماره ركورد كنفرانس :
3208
عنوان مقاله :
Adaptive IMMPF for Bearing-Only Maneuvering Target Tracking in Wireless Sensor Networks
پديدآورندگان :
Khaloozadeh, Hamid Department of Systems and Control - Faculty of Electrical Engineering - K. N. Toosi University of Technology , Keshavarz-Mohammadiyan, Atiyeh Department of Systems and Control - Faculty of Electrical Engineering - K. N. Toosi University of Technology
كليدواژه :
Resampling , Maneuverng Target Tracking , Interacting Multiple Model , Wireless Sensor Network , Adaptive Particle Filter
عنوان كنفرانس :
چهارمين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
Abstract—In this paper, the problem of maneuvering target
tracking in a bearing-only Wireless Sensor network (WSN) is
considered. To estimate the state variables of the moving target
with nonlinear dynamics, Particle Filter (PF) is applied.
Moreover, Interacting Multiple Model (IMM) algorithm is
used to cope with target maneuvers. To reduce the
computational cost of Interacting Multiple Model Particle
Filter (IMMPF) algorithm, a novel adaptive sample set size is
proposed based on the output estimation error. Besides, a new
resampling method is suggested to deal with varying number
of samples. The estimation results of the proposed adaptive
IMMPF are compared with that of IMMPF with fixed number
of samples, in terms of accuracy and computation time.
