The implementation and evaluation of a Kalman filter in MIAS

Master thesis (1993)

Authors

D.J. Moelker

Contributors

E.J. Breeuwer (mentor)

M.A. Salzmann (mentor)

Department

Telecommunicatie- en Verkeersbegeleidingssystemen () (TU Delft)

Accuracy Reliability Kalman filter Optimal filtering (weighted) least squares estimation Approach and landing MLS Integrated Approach System (MIAS)

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http://resolver.tudelft.nl/uuid:57cc1609-b6b6-4dd1-8646-3467e2f4515c

Published Date

1993-06

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Telecommunicatie- en Verkeersbegeleidingssystemen

Abstract

This report describes least squares estimation (LSE) and Kalman filtering in integrated navigation. The Kalman filter and its underlying principles are treated. The implementation of a Kalman filter in MIAS is investigated, and two different Kalman filters are developed. The problems that occur in a hybrid environment as the asynchronicity of the measurement sources and correction for sensor displacement from the aircraft center of gravity are solved. A flight test is performed to test MIAS. This flight test forms the basis for an analysis that is done to evaluate the performance of the two Kalman filters relative to weighted least squares estimation. These results indicate that MIAS can satisfy CAT III landing system requirements without DME/P, while the Kalman filter gives a relative improvement of accuracy at far range from the MLS datum point with respect to the weighted least squares estimator.

Files

AA278854_5.pdf

(pdf | 4.46 Mb)