DocumentCode :
3392977
Title :
A self-calibration filter based on semi-parameter modeling and DUKF
Author :
Ye, Liu ; Xi-Long, Sun ; Ju-Bo, Zhu ; Dian-Nong, Liang
Author_Institution :
Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2010
fDate :
24-28 Oct. 2010
Firstpage :
219
Lastpage :
222
Abstract :
Compensations or eliminations of the systematical error are indispensable for designing an accurate real-time instrumental system. In virtue of an elaborate object function, a new recursive model for the state and the systematical error is developed based on semi-parameter modeling. Considering of the separable character of the new model, an improved dual unscented filter (DUKF) is developed, which can estimate the state and the systematical error simultaneously. The new algorithm has excellent self-calibration ability for the systematical error as well as a marked accuracy of the state estimation, which are validated by simulations.
Keywords :
filtering theory; recursive estimation; state estimation; DUKF; accurate real-time instrumental system; elaborate object function; improved dual unscented filter; recursive model; self-calibration ability; self-calibration filter; semiparameter modeling; separable character; state estimation; systematical error; Equations; Estimation; Information filters; Kalman filters; Mathematical model; Real time systems; dual unscented Filter; self-calibration; semi-parameter modeling; systematical error;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing (ICSP), 2010 IEEE 10th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-5897-4
Type :
conf
DOI :
10.1109/ICOSP.2010.5655196
Filename :
5655196
Link To Document :
بازگشت