Abstract:
Current underwater acoustic channel estimation techniques generally apply linear
MMSE estimation. This approach is optimal in a mean square error sense under the
assumption that the impulse response fluctuations are well characterized by Gaussian
statistics, leading to a Rayleigh distributed envelope. However, the envelope statistics
of the underwater acoustic communication channel are often better modeled by the
K-distribution. In this thesis, by presenting and analyzing field data to support this
claim, I demonstrate the need to investigate channel estimation algorithms that exploit
K-distributed fading statistics. The impact that environmental conditions and
system parameters have on the resulting distribution are analyzed. In doing so, the
shape parameter of the K-distribution is found to be correlated with the source-to-receiver
distance, bandwidth, and wave height. Next, simulations of the scattering
behavior are carried out in order to gain insight into the physical mechanism that
cause these statistics to arise. Finally, MAP and MMSE based algorithms are derived
assuming K-distributed fading models. The implementation of these estimation algorithms
on simulated data demonstrates an improvement in performance over linear
MMSE estimation.
