Limitations of nonlinear chaotic dynamics in predicting sea clutter returns

The ability to describe sea clutter returns via nonlinear, and more specifically chaotic, dynamics is examined. It is shown that the commonly used chaotic invariant measures of correlation dimension and Lyapunov exponent are incapable of uniquely identifying chaotic processes, and produce similar results for measured sea clutter returns and simulated stochastic processes. The potential existence of an underlying chaotic texture masked by stochastic overlying speckle is examined but found to be inconsistent with the measured properties of the sea clutter data. Finally, the performance of three linear and nonlinear predictors is tested against high-resolution measured sea clutter data but no improvement is found to exist for the nonlinear predictor tested with respect to linear prediction performance.