Title :
Observable degree analysis for tracking
Author :
Xiao Yang ; Xinsheng Huang ; Shengjian Bai ; Qiang Fang ; Xiabin Dong
Author_Institution :
Coll. of Mechatron. Eng. & Autom., Nat. Univ. of Defense Technol., Changsha, China
Abstract :
An analysis of the observable degree of two tracking system is presented. It is shown that through the method based on mutual information, we can calculate the exact degree of observability of the system states and determine the estimation performance of the extended kalman filter(EKF) and particle filter(PF). Simulation results demonstrate the validity of the method.
Keywords :
Kalman filters; nonlinear filters; observability; particle filtering (numerical methods); state estimation; target tracking; EKF; PF; estimation performance; extended kalman filter; mutual information; observable degree analysis; particle filter; system states observability degree; tracking system; Eigenvalues and eigenfunctions; Estimation; Filtering theory; Information filters; Information theory; Observability; Bearing-only Tracking; Extended Kalman Filter(EKF); Information Theory; Observable Degree; Particle Filter(PF);
Conference_Titel :
Chinese Automation Congress (CAC), 2013
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-0332-0
DOI :
10.1109/CAC.2013.6775764
