Title :
Joint estimation and identification for stochastic systems with unknown inputs
Author :
Hua Lan ; Yan Liang ; Feng Yang ; Zengfu Wang ; Quan Pan
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
Abstract :
Motivated by tracking a manoeuvring target in electronic counter environments, the authors present the problem of joint estimation and identification of a class of discrete-time stochastic systems with unknown inputs in both the plant and sensors. Based on the expectation-maximum criterion, the joint optimisation scheme of state estimation, parameter identification and iteration terminate decision were derived. A numerical example of tracking a manoeuvring target accompanied range gate pull-off is utilised to verify the proposed scheme.
Keywords :
discrete time systems; expectation-maximisation algorithm; optimisation; parameter estimation; state estimation; stochastic systems; target tracking; discrete-time stochastic systems; electronic counter environments; expectation-maximum criterion; iteration terminate decision; joint estimation; joint identification; joint optimisation scheme; manoeuvring target tracking; parameter identification; state estimation;
Journal_Title :
Control Theory & Applications, IET
DOI :
10.1049/iet-cta.2013.0996