Information-Theoretic Analysis of Transient Multi-Aspect Scattering

Information theory is applied to the problem of multi-aspect, time-domain scattering from a general target. The statistical variation of the scattered fields with variable target-sensor orientation is characterized via a hidden Markov model (HMM), a state of which corresponds to a generally contiguous set of target-sensor orientations over which the angular-dependent scattered fields are stationary. The statistical variation of the transient waveforms within each HMM state is modeled via a Markov model, using a wavefront, resonance and time-delay alphabet. The HMM-Markov model is discussed, and applied to a classification problem involving measured acoustic scattering data. Moreover, the statistical model is used to constitute information-theoretic performance bounds on various aspects of the multi-aspect classification problem.