Title :
Fast automatic leveling subject to abrupt deterministic input
Author :
Lee, Sou-chen ; Liu, Cheng-Yu
Author_Institution :
Dept. of Syst. Eng., Chung Cheng Inst. of Technol., Taoyuan, Taiwan
fDate :
7/1/1999 12:00:00 AM
Abstract :
This investigation applies a modified Kalman filter with a recursive generalized M estimator (GME) of input to a class of leveling problems, that are subject to abrupt environmental disturbances and high noise levels. A least-squares estimator (LSE) based hypothetical testing scheme is also devised to detect the onset and presence of the input. Simulation results demonstrate that the leveling speed of convergence and accuracy is markedly higher than the original unmodified one
Keywords :
Kalman filters; accelerometers; aerospace simulation; attitude control; inertial navigation; least squares approximations; position control; recursive estimation; abrupt deterministic input; abrupt environmental disturbances; accelerometer; angular error; correlated force; fast automatic leveling; fourth-order inertial platform dynamic model; high accuracy; high noise levels; hypothetical testing scheme; least-squares estimator; leveling speed of convergence; modified Kalman filter; navigation error; recursive generalized M estimator; simulation; strapdown INS; Accelerometers; Aircraft navigation; Azimuth; Convergence; Least squares approximation; Marine vehicles; Recursive estimation; Sea measurements; Testing; Working environment noise;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on