Nonlinear Dynamics of Sea Clutters and Detection of Small Targets

Abstract

This chapter presents the problem of determining sea clutter dynamics with application to detecting and classifying small targets. A systematic method of reconstruction of a sea clutter attractor is considered. We explore the use of dynamical system techniques, optimization methods and statistical methods to estimate the dynamical characteristics of sea clutters. We assume that the radar information is in the form of a nonlinear time series. Then we sequentially apply a dynamical approach for characterizing radar signals, based on nonlinear estimation of dynamical characteristics, forming the vector of these characteristics, and modelling the evolution of dynamical processes over time. We consider an optimization method for reconstructing parameter spaces of dynamical systems. These techniques can be applied to systems with one or more hidden variables, and can be used to reconstruct maps or differential equations of the sea clutter dynamics. The possible use of chaotic models for development of classical and quantum detector signals is discussed. The systems analysis based methods are illustrated using numerically generated data and radar data previously recorded from experimental radar systems. The dynamical characteristics can be used to better visualize the ‘state vector’ of the radar signal and for the purpose of pattern recognition