Title :
A novel maneuvering target passive tracking algorithm with multiple infrared observers
Author :
Wu, Panlong ; Li, Xingxiu
Author_Institution :
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Abstract :
A novel algorithm of UKF-IMM(unscented Kalman filter-interacting multiple model) is proposed to track a maneuvering target with two infrared observers. This algorithm use Markov process to describe switching probability among the models, while weighting means of inputs and outputs of UKF. The simulations of the application of UKF-IMM and EKF-IMM algorithm to maneuvering target tracking using dual infrared sensors are done separately. The simulation results show that the new algorithm outperforms EKF-IMM in terms of tracking accuracy and filter credibility.
Keywords :
Kalman filters; Markov processes; infrared detectors; probability; target tracking; Markov process; UKF-IMM; dual infrared sensors; filter credibility; infrared observers; multiple infrared observers; switching probability; target passive tracking algorithm; unscented Kalman filter-interacting multiple model; Automation; Covariance matrix; Equations; Filtering algorithms; Infrared sensors; Kalman filters; Markov processes; Passive filters; Predictive models; Target tracking; UKF-IMM; infrared observers; passive tracking;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234699