Characterization of Compact Directional Sensors: Method and Applications
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Boufarah, Eddy Georges
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Abstract
Determining the direction of sound waves with an array of hydrophones at low frequencies may be impractical in many applications due to the requirement of a large aperture. As an alternative, vector sensors are compact devices that yield directional information by measuring the acoustic pressure and all three particle velocity components using a hydrophone and a three-axis accelerometer respectively. The main advantage of using vector sensors is their sensitivity to directional information and their ease of deployment in small systems. Vector sensors’ performance should be improved by accurately calibrating them since measurements of the recorded velocity components are used for direction finding. To this end, this thesis presents a method for calibrating vector sensors with the aid of a Laser Doppler Vibrometer (LDV) and an electrodynamic shaker. For each accelerometer channel, the aim is to determine a frequency dependent sensitivity, which affects the source bearing angle calculated in real settings. A numerical simulation is conducted to quantify the error in direction finding based on a vector sensor’s sensitivity functions.
A linear least-squares formulation for self-localization of mobile platforms equipped with time- synchronized vector sensors is also presented as an extension to previous work on this topic. This self-localization method uses a source of opportunity to localize a platform of unknown trajectory with respect to another platform whose position is known. Knowledge of the bearing and azimuth angles of the received wave on each platform and the source’s time delay of arrival, obtained from vector sensor recordings, are prerequisites for implementing this method. The proposed self-localization method was tested through
numerical simulations and experimentally using vector sensors’ recordings of data near the Atlantis II seamounts in the Northwest Atlantic
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Date
2025-05-02
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Text
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Thesis (Masters Degree)