DocumentCode
3076889
Title
Passive Multi-sensor Maneuvering Target Tracking Based on UKF-IMM Algorithm
Author
Wu, Panlong ; Li, Xingxiu
Author_Institution
Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
Volume
2
fYear
2009
fDate
10-11 July 2009
Firstpage
135
Lastpage
138
Abstract
For effectively improving the accuracy of tracking a maneuvering target by passive sensors, a novel passive multi-sensor maneuvering target tracking algorithm based on unscented Kalman filter-interacting multiple model (UKF-IMM) is proposed. In this algorithm UKF is used by all models. UKF can avoid linearization of the highly nonlinear equations, and achieve accuracy at least to the second order. This algorithm use Markov process to describe switching probability among the models, while weighting means of inputs and outputs of UKF. Simulation results in passive maneuvering target tracking using three infrared sensors show that the proposed algorithm is more stable and effective.
Keywords
Kalman filters; Markov processes; nonlinear equations; sensor fusion; target tracking; Markov process; UKF-IMM algorithm; nonlinear equations; passive multisensor maneuvering target tracking; unscented Kalman filter-interacting multiple model; Automation; Covariance matrix; Filtering algorithms; Information filtering; Jacobian matrices; Kalman filters; Markov processes; Nonlinear systems; Sensor systems; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location
Taiyuan, Shanxi
Print_ISBN
978-0-7695-3679-8
Type
conf
DOI
10.1109/ICIE.2009.182
Filename
5211450
Link To Document