Information theoretic/chaotic sonar signal processing

Abstract

Dynamical systems generate complex signals. Very often, traditional sonar signal processing in both the time domain and frequency domain are not adequate enough to characterize the complex dynamics of underwater sources that generate, radiate and/or reflect sonar signals. Recent advances in signal processing are aimed at capitalizing on the inherent complexities in a signal structure by applying information theoretic/chaotic processing analysis tools to reveal signal dynamics, otherwise unseen when traditional (linear) signal processing methods are applied. Here examples are presented of periodicities (i.e., limit cycles), quasi-periodicites (2-torus and n-torus motion) and nonperiodic (chaotic) motion as applied to signals-of-interest in underwater acoustic applications. It is demonstrated how nonlinear diagnostic tools, when appropriately applied to underwater acoustic time series measurements, can be used for extracting new information about system dynamics.