TY - JOUR
T1 - Unscented incremental filter method
AU - Fu, Hui Min
AU - Lou, Tai Shan
AU - Wu, Yun Zhang
PY - 2012/7
Y1 - 2012/7
N2 - The unscented incremental filter (UIF) model and analysis method were put forward, in which its concept, basis equations and the recursive calculative steps were established, and special concern was given to UIF with additive noise. In practice, the measurement data have unknown system errors, for the environmental factors, the instability of measurement equipments and the improper models and parameters. Under these conditions, the classic unscented Kalman filter (UKF) have greater filtering error, and even lead to diverge. The presented UIF can successfully eliminate these unknown system errors and improve the filtering accuracy. The method is simple to calculate and easy to apply in engineering.
AB - The unscented incremental filter (UIF) model and analysis method were put forward, in which its concept, basis equations and the recursive calculative steps were established, and special concern was given to UIF with additive noise. In practice, the measurement data have unknown system errors, for the environmental factors, the instability of measurement equipments and the improper models and parameters. Under these conditions, the classic unscented Kalman filter (UKF) have greater filtering error, and even lead to diverge. The presented UIF can successfully eliminate these unknown system errors and improve the filtering accuracy. The method is simple to calculate and easy to apply in engineering.
KW - Deep space exploration
KW - Filtering accuracy
KW - Incremental measurement equation
KW - System error
KW - Unscented Kalman filter (UKF)
KW - Unscented incremental filter (UIF)
UR - https://www.scopus.com/pages/publications/84865984025
M3 - 文章
AN - SCOPUS:84865984025
SN - 1000-8055
VL - 27
SP - 1625
EP - 1629
JO - Hangkong Dongli Xuebao/Journal of Aerospace Power
JF - Hangkong Dongli Xuebao/Journal of Aerospace Power
IS - 7
ER -