Title :
Adaptive model architecture and extended Kalman-Bucy filters
Author_Institution :
Center for Appl. Math., St. Thomas Univ., St. Paul, MN, USA
fDate :
4/1/1994 12:00:00 AM
Abstract :
In radar systems, extended Kalman-Bucy filters (EKBFs) are used to estimate state vectors of objects in track. Filter models accounting for fundamental aerodynamic forces on reentry vehicles are well known. A general model structure accommodating the dynamics of reentry vehicles in both exoatmospheric and endoatmospheric flight is presented. The associated EKBFs for these various models are described and the resulting associated parameter estimation and identification problems are discussed. The effects of position, velocity, drag, and aerodynamic lift are described within a nested set of EKBF models
Keywords :
Kalman filters; adaptive filters; aerodynamics; parameter estimation; remote sensing by radar; signal detection; tracking; aerodynamic forces; aerodynamic lift; drag; dynamics of reentry vehicles; endoatmospheric flight; exoatmospheric flight; extended Kalman-Bucy filters; filter models; general model structure; identification; position; radar systems; reentry vehicles; state vectors estimation; velocity; Adaptive filters; Aerodynamics; Automotive engineering; Navigation; Radar applications; Radar tracking; Sensor phenomena and characterization; Surveillance; Vehicle dynamics; Vehicles;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on