Title :
Adaptive filter for linear systems with generalized unknown disturbance in measurements
Author :
Yanbo Yang ; Yuemei Qin ; Yan Liang ; Quan Pan ; Feng Yang
Author_Institution :
Sch. of Autom., Northwestern Polytech. Univ., Xian, China
Abstract :
The paper presents the problem of state estimation of linear stochastic time-varying system with generalized unknown disturbance (GUD) existing in the measurements. Such GUD can reflect the effects of sensor bias, deception jamming, navigation bias and so on. An upper-bound filter (UBF) is designed for such systems, and its optimal parameters are derived so that the minimum upper-bounds filter (MUBF) is obtained. The simulation about tracking a target via a biased sensor shows the effectiveness of the proposed filter.
Keywords :
adaptive filters; linear systems; state estimation; stochastic systems; GUD; MUBF; adaptive filter; biased sensor; deception jamming; generalized unknown disturbance; linear stochastic time-varying system; minimum upper-bounds filter; navigation bias; optimal parameters; sensor bias; state estimation; upper-bound filter; Noise; Optimized production technology; Robustness; State estimation; Target tracking; Technological innovation; Vectors; Adaptive filtering; discrete time systems; generalized unknown disturbance;
Conference_Titel :
Information Fusion (FUSION), 2013 16th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-605-86311-1-3
