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Evaluation of Matched-Field Processing Techniques Using Simulated Acoustic Vector Sensor Data

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Master's thesis

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There has recently been growing interest in the use of acoustic particle velocity measurements for sonar system applications such as source localization. It is expected that acoustic particle velocity sensors or vector sensors have the potential to improve the performance of scalar acoustic pressure sensors. Although extensive research has been performed to study the enhancements for plane-wave beamforming, little has been done in the more general area of matched-field processing. Some researchers maintain that the collective performance of pressure sensors in an array is equivalent to that of vector sensors, i.e. measuring the three components of acoustic particle velocity in addition to pressure however, this position has not been proven conclusively. This thesis serves to provide insight into possible improvements in matched-field processing performance realizable through the use of vector sensors. First, a proven numerical method is used to simulate an acoustic field. The field observed at an array of vector sensors and their predicted replica fields are correlated in order to localize a continuous-wave point source at an arbitrary but known depth and distance. The comparison of performance is carried out using an Ambiguity Surface, as is typically done in linear Bartlett matched-field processing techniques, at 1000 Hz. The level of performance is further evaluated in the presence of different environments, source positions and perturbations. Through the use of the developed matched-field processor verified with known theory, this thesis concluded that the performance of a vector sensor array is not clearly superior to a hydrophone array of similar specifications. In the environments investigated, no improvement in performance was demonstrated for the vector sensor array over that expected for an array consisting of pressure sensors alone.

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  • Acoustic Detection and Detectors

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