A spatial temporal dynamical model for multipath scattering from the sea

Abstract

new method for modeling sea scattered signals is proposed in this paper. Instead of using a probabilistic model, a spatial temporal dynamical model is employed to model the sea scatter phenomenon. Our approach is empirical in the sense that a model is constructed based on experimental data. We extend the approach of using a temporal predictor for temporal dynamical system reconstruction to a spatial temporal predictor for reconstructing a spatial temporal one. The basic spatial temporal dynamical model used in this study is a couple map lattice (CML) rather than the conventional partial differential equation. The Radial Basis Function (RBF) neural network is incorporated into the CML to enhance the function approximation ability, and the autocorrelation function is used to determine the spatial effect across individual channel. An array antenna was used to collect real spatial temporal sea scattered data for this study. Preliminary results shows that the new model provides an accurate description of the sea scattered signals, and has the potential for signal processing applications.