Blind deconvolution in multipath environments and extensions to remote source localization

In the ocean, the acoustic signal from a remote source recorded by an underwater hydrophone array is commonly distorted by multipath propagation. Blind deconvolution is the task of determining the source signal and the impulse response from array-recorded sounds when the source signal and the environment’s impulse response are both unknown. Synthetic time reversal (STR) is a passive blind deconvolution technique that accomplishes two remote sensing tasks. 1) It can be used to estimate the original source signal and the source-to-array impulse responses, and 2) it can be used to localize the remote source when some information is available about the acoustic environment. The performance of STR for both tasks is considered in this thesis. For the first task, simulations and underwater experiments (CAPEx09) have shown STR to be successful for 1.5-4 kHz broadcast signal. Here STR is successful when the signal-to-noise ratio is high enough, and the receiving array has sufficient aperture and element density so that conventional delay-and-sum beamforming can be used to distinguish ray-path-arrival directions. Also, an unconventional beamforming technique (frequency-difference beamforming) that manufactures frequency differences from the recorded signals has been developed. It allows STR to be successful with sparse array measurements where conventional beamforming fails. Broadband simulations and experimental data from the focused acoustic field experiment (FAF06) have been used to determine the performance of STR when combined with frequency-difference beamforming. For the source localization task, the STR-estimated impulse responses may be combined with ray-based back-propagation simulations and the environmental characteristics at the array into a computationally efficient scheme that localizes the remote sound source. These localization results from STR are less ambiguous than those obtained from conventional matched field processing in the same bandwidth. However, when the frequency of the recorded signals is sufficiently low and close to modal cutoff frequencies, STR-based source localization may fail because of dispersion in the environment. For such cases, an extension of mode-based STR has been developed for sound source ranging with a vertical array in a dispersive underwater sound channel using bowhead whale calls recorded with a 12-element vertical array (Arctic 2010).PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102443/1/shimah_1.pd

Theory and Application of Autoproducts

Acoustics is a branch of physics largely governed by linear field equations. Linearity carries with it the implication that only the frequencies broadcast by acoustic sources can be measured in the surrounding acoustic medium. However, nonlinearities introduced not in the physical world, but in the mathematical and signal processing realm, have the potential to change frequency content. In this dissertation, nonlinear mathematical constructions termed ‘autoproducts’ are created which have the potential to shift frequencies from the measured, in-band frequencies to other higher or lower frequencies which may no longer be in-band. These out-of-band autoproduct fields did not physically propagate in the environment, and yet, this research has found that autoproducts can nonetheless mimic genuine out-of-band fields in a number of different acoustic environments. Approximately half of this dissertation addresses the theory of autoproducts. More specifically, mathematical analyses and simple acoustic models are used to uncover the reasons for how this frequency-shifting behavior works, and what its limitations are. It is found that there are no inherent limitations on the frequencies considered, and that in single-path environments, like plane or spherical waves, autoproducts mimic out-of-band fields in all or nearly all circumstances, respectively. However, in multipath environments, the mimicry of out-of-band fields by autoproducts is no longer so complete. Though, with bandwidth averaging techniques, it is found that the difference in time-of-arrivals of multiple paths is an important parameter: if it is larger than the inverse of the bandwidth available for averaging, then autoproducts can succeed in mimicking out-of-band fields. Other theoretical considerations include the effects of diffraction behind barriers and the effects of strong refraction. Strengths and limitations of autoproducts are assessed with a variety of simple acoustic models, and conclusions are drawn as to the predicted capabilities of autoproduct-based techniques. The other half of this dissertation covers applications of autoproducts. More specifically, it focuses on the use of autoproducts to perform physics-based source localization, especially for applications in the shallow ocean. Existing techniques are well-known to be very sensitive to uncertainties in the acoustic environment (e.g. the sound speed), especially at high frequencies (nominally greater than 1 kHz in the shallow ocean). Through the use of autoproducts, measured fields at high frequency can be shifted to much lower frequencies, where they can be processed with much more robustness to environmental uncertainties. In one of the main results of this dissertation, it is shown that a remote acoustic source broadcasting sound between 11 and 33 kHz in a 106-meter-deep, downward refracting sound channel could be localized using measurements from a sparse array located 3 km away. The data from the method suggest that autoproduct-based source localization can make physics-based array signal processing robust at arbitrarily high frequencies – a novel and important contribution to existing literature. Overall, by developing the theory for, and exploring applications of, these nonlinear mathematical constructions, the extent to which autoproducts are fundamentally limited is assessed, and new signal processing techniques are developed which have the potential to significantly improve the robustness of source localization algorithms for uncertain multipath environments. Through this study, significant portions of the necessary theoretical foundation have been laid, which will aid in the further development of robust, autoproduct-based signal processing techniques.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145865/1/bworthma_1.pd

Effects of errorless learning on the acquisition of velopharyngeal movement control

Session 1pSC - Speech Communication: Cross-Linguistic Studies of Speech Sound Learning of the Languages of Hong Kong (Poster Session)The implicit motor learning literature suggests a benefit for learning if errors are minimized during practice. This study investigated whether the same principle holds for learning velopharyngeal movement control. Normal speaking participants learned to produce hypernasal speech in either an errorless learning condition (in which the possibility for errors was limited) or an errorful learning condition (in which the possibility for errors was not limited). Nasality level of the participants’ speech was measured by nasometer and reflected by nasalance scores (in %). Errorless learners practiced producing hypernasal speech with a threshold nasalance score of 10% at the beginning, which gradually increased to a threshold of 50% at the end. The same set of threshold targets were presented to errorful learners but in a reversed order. Errors were defined by the proportion of speech with a nasalance score below the threshold. The results showed that, relative to errorful learners, errorless learners displayed fewer errors (50.7% vs. 17.7%) and a higher mean nasalance score (31.3% vs. 46.7%) during the acquisition phase. Furthermore, errorless learners outperformed errorful learners in both retention and novel transfer tests. Acknowledgment: Supported by The University of Hong Kong Strategic Research Theme for Sciences of Learning © 2012 Acoustical Society of Americapublished_or_final_versio

Mobile underwater acoustic communications with multicarrier modulation in very shallow waters

Master'sMASTER OF ENGINEERIN

Analysis of and techniques for adaptive equalization for underwater acoustic communication

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2011Underwater wireless communication is quickly becoming a necessity for applications in ocean science, defense, and homeland security. Acoustics remains the only practical means of accomplishing long-range communication in the ocean. The acoustic communication channel is fraught with difficulties including limited available bandwidth, long delay-spread, time-variability, and Doppler spreading. These difficulties reduce the reliability of the communication system and make high data-rate communication challenging. Adaptive decision feedback equalization is a common method to compensate for distortions introduced by the underwater acoustic channel. Limited work has been done thus far to introduce the physics of the underwater channel into improving and better understanding the operation of a decision feedback equalizer. This thesis examines how to use physical models to improve the reliability and reduce the computational complexity of the decision feedback equalizer. The specific topics covered by this work are: how to handle channel estimation errors for the time varying channel, how to use angular constraints imposed by the environment into an array receiver, what happens when there is a mismatch between the true channel order and the estimated channel order, and why there is a performance difference between the direct adaptation and channel estimation based methods for computing the equalizer coefficients. For each of these topics, algorithms are provided that help create a more robust equalizer with lower computational complexity for the underwater channel.This work would not have been possible without support from the O ce of Naval Research, through a Special Research Award in Acoustics Graduate Fellowship (ONR Grant #N00014-09-1-0540), with additional support from ONR Grant #N00014-05- 10085 and ONR Grant #N00014-07-10184

Interferometric Synthetic Aperture Sonar Signal Processing for Autonomous Underwater Vehicles Operating Shallow Water

The goal of the research was to develop best practices for image signal processing method for InSAS systems for bathymetric height determination. Improvements over existing techniques comes from the fusion of Chirp-Scaling a phase preserving beamforming techniques to form a SAS image, an interferometric Vernier method to unwrap the phase; and confirming the direction of arrival with the MUltiple SIgnal Channel (MUSIC) estimation technique. The fusion of Chirp-Scaling, Vernier, and MUSIC lead to the stability in the bathymetric height measurement, and improvements in resolution. This method is computationally faster, and used less memory then existing techniques

Robust acoustic signal detection and synchronization in a time varying ocean environment

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 2012Signal detection and synchronization in the time varying ocean environment is a difficult endeavor. The current common methods include using a linear frequency modulated chirped pulse or maximal length sequence as a detection pulse, then match filtering to that signal. In higher signal to noise ratio (SNR) environments (~0 dB and higher) this has been a suitable solution. As the SNR drops lower however, this solution no longer provides an acceptable probability of detection for a given tolerable probability of false alarm. The issue derives from the inherent coherence issues in the ocean environment which limit the useful matched filter length. This thesis proposes an alternative method of detection based on a recursive least squares linearly adaptive equalizer which we term the Adaptive Linear Equalizer Detector (ALED). This detectors performance has demonstrated reliable probability of detection with minimal interfering false alarms with SNR as low as -20 dB. Additionally this thesis puts forth a computationally feasible method for implementing the detector.Support from the Office of Naval Research (through ONR grant #N00014-07-10738 and #N00014-11-10426)