NDLI: Two time scale discrete Kalman filter design for an F-8 aircraft

Content Provider	IEEE Xplore Digital Library
Author	Oloomi, H.M. Pomalaza-Raez, C.
Copyright Year	1990
Description	Author affiliation: Dept. of Eng., Indiana Univ., Fort Wayne, IN, USA (Oloomi, H.M.)
Abstract	We consider the stochastic model of an F8 aircraft linearized about some flight condition. The process and observation noise vectors are assumed to be zero mean white Gaussian processes of appropriate intensities. After sampling the system with an allowable sampling period, the dynamics of the aircraft and the observation vector are expressed in the sampled-data form. Our goal is to optimally estimate the states of the aircraft by means of minimizing the mean squared error on the basis of the observed output. Although the optimal solution to the problem can be furnished by a standard Kalman filter, the implementation of this solution requires an estimator which incorporates a full order Riccati equation. Unfortunately, due to the speed and memory limitations of the flight computer, this solution is not practically feasible. Therefore, any reduction in the size of computation is highly desirable if the Kalman filter solution is to be implemented in real time. Moreover, the standard Kalman filter solution is ill-conditioned since the magnitude of the noise covariance matrices are inversely proportional to the small sampling period, making the magnitude of the covariance matrices relatively large compared to those of the system matrices. Consequently, serious numerical difficulties are expected if the filter gain coefficients are to be computed on the basis of the full order Riccati equation. We propose a technique which alleviates both the high dimensionality and the ill-conditioning associated with the problem. Our approach is based on the singular perturbation results.
Starting Page	517
Ending Page	522
File Size	508828
Page Count	6
File Format	PDF
ISBN	0780336585
DOI	10.1109/TCC.1996.561124
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-04-30
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Aircraft Riccati equations Sampling methods Covariance matrix Stochastic resonance Gaussian noise Gaussian processes State estimation Computer errors Filters
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in