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Proceedings Paper

Kalman filtering approach for reducing gyroscope noise effects in stabilized platforms
Author(s): Marcelo C. Algrain
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Paper Abstract

Stabilization systems use gyroscopes typically mounted along side sensing or imaging devices being isolated from external rotations in inertial space. The gyroscopes measure the residual angular motion of the platform stabilized member. The better the stabilization the smaller the sensed residual motion is. Conceivably, the residual motion (angular jitter) could be as small as the noise in the gyroscope outputs. This represents a low signal-to-noise ratio case. Under such conditions, lower noise gyroscopes would be required to further reduce angular jitter, at considerably higher expense. Alternatively, the performance of the stabilization system can be significantly enhanced through noise reducing optimal filtering techniques. The latter approach uses angular velocity estimates that are more accurate than raw measurements to stabilize the platform, without resorting to more precise and costly lower-noise gyroscopes. This paper presents a new Kalman filtering technique that reduces the mean-square-error (MSE) between actual angular velocity values and estimated ones by an order of magnitude (when compared to the MSE resulting from direct measurements) even under extremely low signal-to-noise ratio conditions. The electronically improved angular motion measurements can be fed into the platform stabilization control system (instead of raw measurements) considerably reducing stabilization jitter.

Paper Details

Date Published: 25 November 1992
PDF: 15 pages
Proc. SPIE 1697, Acquisition, Tracking, and Pointing VI, (25 November 1992); doi: 10.1117/12.138192
Show Author Affiliations
Marcelo C. Algrain, Univ. of Nebraska/Lincoln (United States)

Published in SPIE Proceedings Vol. 1697:
Acquisition, Tracking, and Pointing VI
Michael K. Masten; Larry A. Stockum, Editor(s)

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