ECE Seminar Series Fall 2014
Thursday October 2nd, 1-2 PM, ITEB 336
Time varying and sparse underwater acoustic response estimation via a hierarchical Gaussian mixture model with application to M-ary orthogonal spread spectrum signaling
Paul J. Gendron
University of Massachusetts Dartmouth
Abstract: Recent advances in modeling doubly spread propagation channels have provided solutions for diverse communication applications between mobile platforms and these advances have been extended and have had a positive impact on the particularly challenging underwater acoustic environment. In this talk a hierarchical Gaussian mixture model is proposed to characterize shallow water acoustic response functions that are time-varying and sparse. A particular ocean environment between source and receiver is predicated on a proportion of relatively coherent paths that possess an ensemble frequency-Doppler-beam spectra. Conditioned on the bulk platform speed and ensemble Doppler spread a structured field of Beta variates link the Doppler profile to the probabilities of indicator variables specifying the state of ensonification across channel frequency, Doppler and beam. Conditioned on these indicator variables the amplitude and phase of a particular frequency and Doppler slot is modeled as complex Gaussian. The remaining non-coherent multiple surface scattered paths exhibit a spectrally flat Doppler profile. The hierarchical model is flexible and naturally accommodates diverse platform motion scenarios and array orientations. Accurate estimation of the time-varying acoustic response for the full duration of the broadband transmission facilitates compensation of the bulk time-varying dilation process taking advantage of the correlated coherent paths. The model ameliorates coherence degradation and enhance coherent multi-path combining replacing conventional time recursive Kalman-like schemes for channel estimation and classic PLL structures for phase tracking. A receiver for M-ary orthogonal spread spectrum signaling is built on this model and is tested at very low signal to noise ratios without the aid of pilot symbols. Tests were conducted in shallow water ocean environments in Buzzards Bay MA and St. Margaret’s Bay. Empirical bit error rates are demonstrated at very low SNRs with coherent symbol decisions. Tests were conducted at various spreading gains and bandwidths to achieve rates up to 130 bps at 2 km with a demonstrated probability of bit error less than E-4 with 3 element combining at SNRs less than -20 dB. [This work is funded by the Office of Naval Research, SSC Pacific’s Naval Innovative Science and Engineering Basic and Applied Research Program as well as the University of Massachusetts Dartmouth].
Bio: Paul J. Gendron is an Assistant Professor at the University of Massachusetts Dartmouth. He received his PhD from Worcester Polytechnic Institute, his MS from Virginia Tech and his BS from the University of Massachusetts Amherst, all in Electrical Engineering. His work is broad in the fields of statistical signal processing, detection and estimation theory. His contributions range from seismic event detection and classification where he is the co-developer of the New England Seismic Network’s rapid seismic event detection algorithm to adaptive filtering, underwater acoustic communications and magnetic anomaly detection. In 2000 he was the recipient of an Office of Naval Research Fellowship award for his work with the Acoustics Division at the Naval Research Laboratory and in 2006 he was an Office of Naval Research Visiting Scientist to DRDC-Atlantic, Canada. Paul presently conducts research for the Office of Naval Research and SSC Pacific related to the discovery and invention of enabling technologies for undersea surveillance.
Host: Shengli Zhou, email@example.com