Table of Contents
Preamble
During my academic career, I have published several papers and a thesis. Below is a list of my publications and a brief description of each. The full text of some publications have open access while others unfortunately have more restrictive access.
An Embedded Real-time Passive Underwater Acoustic Localization System using a Compact Sensor Array
Description
This thesis was defended on April 12, 2023 and was published on April 14, 2023 on DalSpace. It was submitted to the Faculty of Graduate Studies at Dalhousie University in partial fulfillment of the requirements for the degree of Master of Applied Science in the Department of Electrical and Computer Engineering. The completion of this thesis was supervised by Dr. Bousquet.
Abstract
In this thesis, a passive underwater acoustic localization system using a compact sensor array is developed which receives underwater acoustic sensor data and outputs the position estimations to a map display in real-time. Through simulation, it is evaluated using 130 kHz pulses, which is representative of the harbour porpoise echolocation clicks. The localization system is tested in several environments including the Aquatron, Bay of Fundy, Herring Cove, and New Zealand. The Time Difference of Arrival localization algorithm is used to estimate the position of sound sources using the difference of propagation time between multiple sensors. The implementation also improves upon a traditional grid search by using a lookup table stored in a hyperoctree to reduce the execution time of a position estimation. Additionally, a method to analyze and reduce the estimation error for different sensor geometries is developed. Finally, the impact of noise is mitigated by using various pre-processing techniques.
Full Text
The full text of the thesis is available for download on DalSpace. The full text is also available for download here (24.8MB).
Harbour Porpoise Localization System Using Compact Acoustic Sensor Arrays
Description
This paper was submitted to the 2022 International Conference on Underwater Networks & Systems (WUWNet’22). It was accepted on October 5, 2022 and published on December 29, 2022 in the Proceedings of the 16th International Conference on Underwater Networks & Systems. The conference was held in Boston, Massachusetts, USA from November 14–16, 2022.
Abstract
The objective of this work is to develop a localization system using a compact array capable of obtaining a coarse estimate of the location of high frequency echolocation pulses emitted by harbour porpoises. This work improves upon a traditional grid search by using a lookup table which is stored in a hyperoctree to reduce the computation time required to perform the localization. Additionally, the impact of the sensor geometry is analysed to improve the accuracy of an existing sensor configuration. Finally, the impact of the noise on the measured signal is analysed and mitigated by using various preprocessing techniques.
Full Text
This paper is available on ACM Digital Library (restrictive access).
Passive Localization Algorithm using a Highly Integrated Acoustic Sensor Array
Description
This paper was submitted to the 2022 20th IEEE Interregional NEWCAS Conference (NEWCAS 2022) and won the 2nd place paper award. It was accepted on September 1, 2022 and published on October 1, 2022 in the Proceedings of the 2022 IEEE 20th International New Circuits and Systems Conference. The conference was held in Québec City, Québec, CA from June 19–22, 2022.
Abstract
This paper proposes a passive localization algorithm that can locate sound sources underwater using a 4-element compact array. Through simulation, its performance is compared to that of a standard time difference of arrival algorithm. The proposed algorithm is implemented in real-time on a System-on-Chip (SoC) which executes the algorithm. The resources and power requirements of the SoC are evaluated. The peripherals are integrated with a controller program running the PetaLinux operating system. Finally, the performance of the implemented real-time system is compared to a MATLAB simulation, which demonstrates the potential for the remote platform to reliably detect marine mammals.
Full Text
This paper is available on IEEE Xplore (restrictive access).
A Remote Sensor for Marine Mammal Localization
Description
This report was prepared with several other authors and submitted to the Offshore Energy Research Association (OERA) in June, 2021. In this report, the following sections had my primary focus:
- 2.7: Real-Time System Architecture
- 2.7.1: Firmware Architecture
- 2.7.2: Real-time Localization Implementation (partial)
- 2.7.3: Verification of the Controller in Test Tanks
Full Text
The full text of the paper is available for download on Offshore Energy Research Association (15.0MB).