Range rate estimation based on geometric feature decomposition

Graham H. Watson; Simon A. Watts; Sharon K. Watson

doi:10.1117/12.364046

4 October 1999 Range rate estimation based on geometric feature decomposition

Graham H. Watson, Simon A. Watts, Sharon K. Watson

Proceedings Volume 3809, Signal and Data Processing of Small Targets 1999; (1999) https://doi.org/10.1117/12.364046
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

A method of estimating relative range rate for airborne targets based on projective geometry is presented, where robustness to noise and clutter is achieved using a wavelet representation. The first stage is to extract simple geometric bar features at multiple resolutions from local extrema in a wavelet transform. These are then refined in position, orientation, scale and aspect ratio to fit regions of the target, for examples wings and fuselage. Affine transformations are then found which map these geometric components between image frames. Finally a relationship between affine transformations and changes in 3D viewing aspect is used to estimate inter-frame range ratio. This method has the robustness of those based on first and second-order moments while retaining sufficient information to unambiguously identify an affine transformation between frames. The method does not depend on region segmentation to define an outline of the target, and is therefore insensitive to noise. Results are presented for 3D simulations of aircraft flying against a background of sky with clouds, where accurate range data are available. Range ratios are accurate over a wide range of 3D target orientations, but errors are more pronounced when new parts of the target become visible.

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Graham H. Watson, Simon A. Watts, and Sharon K. Watson "Range rate estimation based on geometric feature decomposition", Proc. SPIE 3809, Signal and Data Processing of Small Targets 1999, (4 October 1999); https://doi.org/10.1117/12.364046

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KEYWORDS

3D acquisition

Clouds

Image segmentation

Sensors

Feature extraction

Composites

Error analysis

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