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Proceedings Paper

On modeling sea clutter by noisy chaotic dynamics
Author(s): Wen-wen Tung; Jing Hu; Jianbo Gao; Robert S. Lynch; Genshe Chen
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Paper Abstract

Modeling sea clutter by chaotic dynamics has been an exciting yet heatedly debated topic. To resolve controversies associated with this approach, we use the scale-dependent Lyapunov exponent (SDLE) to study sea clutter. The SDLE has been shown to be able to unambiguously distinguish chaos from noise. Our analyses of almost 400 sea clutter datasets measured by Professor Simon Haykin suggest that on very short time scales, sea clutter may be classified as noisy chaos, characterized by a parameter γ, which characterizes the speed of information loss. It is shown that γ can be used to very effectively detect low observable targets within sea clutter.

Paper Details

Date Published: 17 April 2008
PDF: 10 pages
Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 69681G (17 April 2008); doi: 10.1117/12.777204
Show Author Affiliations
Wen-wen Tung, Purdue Univ. (United States)
Jing Hu, Univ. of Florida (United States)
Jianbo Gao, Univ. of Florida (United States)
Robert S. Lynch, Naval Undersea Warfare Ctr. (United States)
Genshe Chen, DCM Research Resources LLC (United States)


Published in SPIE Proceedings Vol. 6968:
Signal Processing, Sensor Fusion, and Target Recognition XVII
Ivan Kadar, Editor(s)

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