Adaptive model architecture and extended Kalman-Bucy filters

Author

Costa, Peter J.

Author_Institution

Center for Appl. Math., St. Thomas Univ., St. Paul, MN, USA

Volume

30

Issue

2

fYear

1994

fDate

4/1/1994 12:00:00 AM

Firstpage

525

Lastpage

533

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;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.272275

Filename

272275