Aiming at the effective realization of particle filter for maneuvering target tracking in multi-sensor measurements,a novel multi-sensor multiple model particle filtering algorithm with correlated noises is proposed.C...Aiming at the effective realization of particle filter for maneuvering target tracking in multi-sensor measurements,a novel multi-sensor multiple model particle filtering algorithm with correlated noises is proposed.Combined with the kinetic evolution equation of target state,a multi-sensor multiple model particle filter is firstly constructed,which is also used as the basic framework of a new algorithm.In the new algorithm,in order to weaken the adverse influence from random measurement noises in the measuring process of particle weight,a weight optimization strategy is introduced to improve the reliability and stability of particle weight.In addition,considering the correlated noise existing in the practical engineering,a decoupling method of correlated noise is given by the rearrangement and transformation of the state transition equation and measurement equation.Since the weight optimization strategy and noise decoupling method adopt respectively the center fusion structure and the off-line way,it improves the adverse effect effectively on computational complexity for increasing state dimension and sensor number.Finally,the theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.展开更多
To track the narrow butt welding seams in container manufacture, a visual tracking system based on smart camera is proposed in this paper. A smart camera is used as the sensor to detect the welding seam. The feature e...To track the narrow butt welding seams in container manufacture, a visual tracking system based on smart camera is proposed in this paper. A smart camera is used as the sensor to detect the welding seam. The feature extraction algorithm is designed with the consideration of the characteristics of the smart caraera, which is used to compute the error between the welding torch and the welding seam. Visual control system based on image is preseated, which employs a programmable controller to control a stepper motor to eliminate the tracking error detected by the smart camera. Experiments are conducted to demonstrate the effectiveness of the vision system.展开更多
基金Supported by the National Natural Science Foundation of China(No.61300214)the National Natural Science Foundation of Henan Province(No.132300410148)+1 种基金the Post-doctoral Science Foundation of China(No.2014M551999)the Funding Scheme of Young Key Teacher ofHenan Province Universities(No.2013GGJS-026)
文摘Aiming at the effective realization of particle filter for maneuvering target tracking in multi-sensor measurements,a novel multi-sensor multiple model particle filtering algorithm with correlated noises is proposed.Combined with the kinetic evolution equation of target state,a multi-sensor multiple model particle filter is firstly constructed,which is also used as the basic framework of a new algorithm.In the new algorithm,in order to weaken the adverse influence from random measurement noises in the measuring process of particle weight,a weight optimization strategy is introduced to improve the reliability and stability of particle weight.In addition,considering the correlated noise existing in the practical engineering,a decoupling method of correlated noise is given by the rearrangement and transformation of the state transition equation and measurement equation.Since the weight optimization strategy and noise decoupling method adopt respectively the center fusion structure and the off-line way,it improves the adverse effect effectively on computational complexity for increasing state dimension and sensor number.Finally,the theoretical analysis and experimental results show the feasibility and efficiency of the proposed algorithm.
文摘To track the narrow butt welding seams in container manufacture, a visual tracking system based on smart camera is proposed in this paper. A smart camera is used as the sensor to detect the welding seam. The feature extraction algorithm is designed with the consideration of the characteristics of the smart caraera, which is used to compute the error between the welding torch and the welding seam. Visual control system based on image is preseated, which employs a programmable controller to control a stepper motor to eliminate the tracking error detected by the smart camera. Experiments are conducted to demonstrate the effectiveness of the vision system.
