
doi: 10.1063/1.166275
pmid: 12779703
The notion that a deterministic nonlinear dynamical system (with relatively few degrees of freedom) can display aperiodic behavior has a strong bearing on sea clutter characterization: random-looking sea clutter may be the outcome of a chaotic process. This new approach envisages deterministic rules for the underlying sea clutter dynamics, in contrast to the stochastic approach where sea clutter is viewed as a random process with a large number of degrees of freedom. In this paper, we demonstrate, convincingly for the first time, the chaotic dynamics of sea clutter. We say so on the basis of results obtained using radar data collected from a series of extensive and thorough experiments, which have been carried out with ground-truthed sea clutter data sets at three different sites. The study includes correlation dimension analysis (based on the maximum likelihood principle) and Lyapunov spectrum analysis. The Lyapunov (Kaplan-Yorke) dimension, which is a byproduct of Lyapunov spectrum analysis, shows that it is indeed a good estimator of the correlation dimension. The Lyapunov spectrum also reveals that sea clutter is produced by a coupled system of nonlinear differential equations of order five or six.
chaotic dynamics, Dimension theory of smooth dynamical systems, Kaplan-Yorke dimension, clutter dynamics, Lyapunov spectrum, Strange attractors, chaotic dynamics of systems with hyperbolic behavior, random process, radar backscatter, stochastic approach, Lyapunov dimension, Time series analysis of dynamical systems
chaotic dynamics, Dimension theory of smooth dynamical systems, Kaplan-Yorke dimension, clutter dynamics, Lyapunov spectrum, Strange attractors, chaotic dynamics of systems with hyperbolic behavior, random process, radar backscatter, stochastic approach, Lyapunov dimension, Time series analysis of dynamical systems
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