Title :
Linearized reduced-order filtering
Author :
Nagpal, Krishan ; Sims, Craig
Author_Institution :
Dept. of Electr. Eng., West Virginia Univ., Morgantown, WV, USA
fDate :
3/1/1988 12:00:00 AM
Abstract :
A reduced-order version of extended Kalman filtering is presented in which both the filtering equation and the associated Riccati equation have been reduced in dimension to allow for real-time processing. The procedure for designing the reduced-order filter is similar to that for designing the extended Kalman filter, the same approximations being applied. One technique useful for limiting the computational burden in a linearized filter design problems is presented and illustrated by an example. The primary limitation of the result is that the nonlinearity must be in terms of the vector to be estimated
Keywords :
Kalman filters; filtering and prediction theory; Kalman filtering; Riccati equation; design; linearized filter; nonlinearity; real-time processing; reduced-order filter; Automatic control; Electrons; Equations; Filtering; Linear systems; Nonlinear filters; Reduced order systems; Root mean square; Stability criteria; State estimation;
Journal_Title :
Automatic Control, IEEE Transactions on