Physically constrained maximum likelihood (PCML) mode filtering and its application as a pre-processing method for underwater acoustic communication
Citable URI
https://hdl.handle.net/1912/3064Location
New Jersey.DOI
10.1575/1912/3064Keyword
Underwater acoustics; Acoustic modelsAbstract
Mode filtering is most commonly implemented using the sampled mode shape or
pseudoinverse algorithms. Buck et al placed these techniques in the context of
a broader maximum a posteriori (MAP) framework. However, the MAP algorithm
requires that the signal and noise statistics be known a priori. Adaptive array processing algorithms are candidates for improving performance without the need for a
priori signal and noise statistics. A variant of the physically constrained, maximum
likelihood (PCML) algorithm is developed for mode filtering that achieves the
same performance as the MAP mode filter yet does not need a priori knowledge of
the signal and noise statistics. The central innovation of this adaptive mode filter is
that the received signal's sample covariance matrix, as estimated by the algorithm,
is constrained to be that which can be physically realized given a modal propagation
model and an appropriate noise model.
The first simulation presented in this thesis models the acoustic pressure field as a
complex Gaussian random vector and compares the performance of the pseudoinverse,
reduced rank pseudoinverse, sampled mode shape, PCML minimum power distortionless response (MPDR), PCML-MAP, and MAP mode filters. The PCML-MAP filter
performs as well as the MAP filter without the need for a priori data statistics. The
PCML-MPDR filter performs nearly as well as the MAP filter as well, and avoids a
sawtooth pattern that occurs with the reduced rank pseudoinverse filter. The second
simulation presented models the underwater environment and broadband communication setup of the Shallow Water 2006 (SW06) experiment. Data processing results
are presented from the Shallow Water 2006 experiment, showing the reduced sensitivity of the PCML-MPDR filter to white noise compared with the reduced rank
pseudoinverse filter. Lastly, a linear, decision-directed, RLS equalizer is used to combine the response of several modes and its performance is compared with an equalizer
applied directly to the data received on each hydrophone.
Description
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2009
Suggested Citation
Thesis: Papp, Joseph C., "Physically constrained maximum likelihood (PCML) mode filtering and its application as a pre-processing method for underwater acoustic communication", 2009-09, DOI:10.1575/1912/3064, https://hdl.handle.net/1912/3064Related items
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