Title :
A new class of efficient adaptive nonlinear filters (ANLF)
Author :
Lainiotis, D.G. ; Papaparaskeva, Paraskevas
Author_Institution :
Intelligent Syst. Technol., Tampa, FL, USA
fDate :
6/1/1998 12:00:00 AM
Abstract :
A multilinearization procedure is described, with the use of which a new class of algorithms for nonlinear filtering can be realized. The methodology targets on adaptively selecting the best reference points for linearization from an ensemble of generated trajectories that span the whole state space of the desired signal. Through simulations, the approach is shown to be significantly superior to the classical extended Kalman filter and comparable in computational burden
Keywords :
adaptive filters; adaptive signal processing; approximation theory; filtering theory; linearisation techniques; nonlinear filters; adaptive nonlinear filters; algorithms; approximate equivalent model; extended Kalman filter; generated trajectories; multilinearization procedure; nonlinear estimation; nonlinear filtering; reference points; signal state space; simulations; Computational modeling; Filtering algorithms; Gaussian noise; Nonlinear filters; Nonlinear systems; Partitioning algorithms; Signal generators; State estimation; State-space methods; Trajectory;
Journal_Title :
Signal Processing, IEEE Transactions on
