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Proceedings Paper

Single-Frame Velocity Estimation
Author(s): James L. Jenkins; Stephen F. Rudin
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Paper Abstract

When 2-D sampled fields of view are generated by staring or scanning arrays of IR detectors, the motion of an unresolved point object is usually measured in terms of changes in position estimates in a series of two or more successive fields, or "frames" of sampled data. However, when motion is pronounced enough to affect data in a single frame, velocity can be estimated from its effect on data. Investigation of motion on the order of 0.10 detector subtense (DS) per detector integration time (DIT) has shown that velocity can be estimated jointly with position to within a small percentage of the actual velocity at a signal to noise ratio (SNR) of 10.0. A linear recursive maximum liklihood estimator, used for position and intensity, is described and extended to encompass the joint estimation of velocity from a single frame of data. Estimation precision is demonstrated by a Monte Carlo approach based on simulation of the estimation process.

Paper Details

Date Published: 5 September 1989
PDF: 6 pages
Proc. SPIE 1096, Signal and Data Processing of Small Targets 1989, (5 September 1989); doi: 10.1117/12.960335
Show Author Affiliations
James L. Jenkins, Aerojet Electrosystems company (United States)
Stephen F. Rudin, Aerojet Electrosystems company (United States)

Published in SPIE Proceedings Vol. 1096:
Signal and Data Processing of Small Targets 1989
Oliver E. Drummond, Editor(s)

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