Estimation and Tracking of Rapidly Time-Varying Broadband Acoustic Communication Channels

Weichang Li, Ph.D., 2006
James Preisig, Advisor

This thesis develops methods for estimating wideband shallow-water acoustic communication channels. The very shallow water wideband channel has three distinct features: large dimension caused by extensive delay spread; limited number of degrees of freedom (DOF) due to resolvable paths and inter-path correlations; and rapid fluctuations induced by scattering from the moving sea surface. Based on state-space channel modeling, the thesis first develops algorithms that jointly estimate the channel and its dynamics, based on the Extended Kalman Filter (EKF) and the Expectation Maximization (EM) approach respectively. Analysis shows conceptual parallels, including an identical second-order innovation form shared by the EKF modification and the suboptimal EM, and the issue of parameter identifiability due to channel structure, reflected as parameter unobservability in EKF and insufficient excitation in EM. A two-model based EKF and a subspace EM algorithm, which selectively track dominant taps and reduce prediction error, are proposed to overcome the identifiability issue. The second part of the thesis develops algorithms that explicitly find the sparse estimate of the delay-Doppler spread function. The study contributes to better understanding of the channel physical constraints on algorithm design and performance improvement. It may be generalized to other applications where dimensionality and variability collide.