The escalating global shift towards sustainable energy sources, particularly wind energy, has accentuated the need for effective measures to mitigate avian fatalities due to the operation of wind turbines. This thesis addresses this pressing ecological issue by enhancing bird tracking in radar systems - a case study on the Birdtrack\textsuperscript{\textregistered} radar system, used in wind farms for avian monitoring and collision prevention. The research presents a novel intersection of technology and ecology, significantly contributing to sustainable energy and wildlife conservation efforts. Central to this research is identifying the existing limitations of the currently adopted Birdtrack\textsuperscript{\textregistered} system in differentiating birds from environmental clutter and accurately tracking multiple birds under dynamic conditions. The methodology employed integrates raw radar data preprocessing, visualization techniques, and the development of robust bird detection and tracking algorithms. Notably, incorporating the Observation-Centric SORT (OC-SORT) algorithm for multi-bird tracking and enhanced radar data processing techniques markedly improves the system detection and tracking precision and efficiency. The effectiveness of the proposed technique is quantified evaluated through case studies in various wind farm environments. Performance metrics such as track velocity, angular trajectory changes, track duration, and quality assessment scores affirm the system superiority over Birdtrack\textsuperscript{\textregistered}. The results demonstrate a significant advancement in tracking accuracy, reduced track fragmentation, and increased detection reliability. The work in this thesis contributes to the improved operation of wind farm systems, while benefiting avian conservation. It addresses the challenges of radar-based bird monitoring and sets a foundation for future research. The successful enhancement of the Birdtrack\textsuperscript{\textregistered} system represents a crucial step in mitigating the environmental impact of wind energy operations, thus aligning sustainable energy production with ecological preservation objectives.

The escalating global shift towards sustainable energy sources, particularly wind energy, has accentuated the need for effective measures to mitigate avian fatalities due to the operation of wind turbines. This thesis addresses this pressing ecological issue by enhancing bird tracking in radar systems - a case study on the Birdtrack\textsuperscript{\textregistered} radar system, used in wind farms for avian monitoring and collision prevention. The research presents a novel intersection of technology and ecology, significantly contributing to sustainable energy and wildlife conservation efforts. Central to this research is identifying the existing limitations of the currently adopted Birdtrack\textsuperscript{\textregistered} system in differentiating birds from environmental clutter and accurately tracking multiple birds under dynamic conditions. The methodology employed integrates raw radar data preprocessing, visualization techniques, and the development of robust bird detection and tracking algorithms. Notably, incorporating the Observation-Centric SORT (OC-SORT) algorithm for multi-bird tracking and enhanced radar data processing techniques markedly improves the system detection and tracking precision and efficiency. The effectiveness of the proposed technique is quantified evaluated through case studies in various wind farm environments. Performance metrics such as track velocity, angular trajectory changes, track duration, and quality assessment scores affirm the system superiority over Birdtrack\textsuperscript{\textregistered}. The results demonstrate a significant advancement in tracking accuracy, reduced track fragmentation, and increased detection reliability. The work in this thesis contributes to the improved operation of wind farm systems, while benefiting avian conservation. It addresses the challenges of radar-based bird monitoring and sets a foundation for future research. The successful enhancement of the Birdtrack\textsuperscript{\textregistered} system represents a crucial step in mitigating the environmental impact of wind energy operations, thus aligning sustainable energy production with ecological preservation objectives.

Eco-Friendly Wind Energy: Improving Radar Tracking Systems for Bird Monitoring

SECA REPAS GONCALVES, DIOGO
2022/2023

Abstract

The escalating global shift towards sustainable energy sources, particularly wind energy, has accentuated the need for effective measures to mitigate avian fatalities due to the operation of wind turbines. This thesis addresses this pressing ecological issue by enhancing bird tracking in radar systems - a case study on the Birdtrack\textsuperscript{\textregistered} radar system, used in wind farms for avian monitoring and collision prevention. The research presents a novel intersection of technology and ecology, significantly contributing to sustainable energy and wildlife conservation efforts. Central to this research is identifying the existing limitations of the currently adopted Birdtrack\textsuperscript{\textregistered} system in differentiating birds from environmental clutter and accurately tracking multiple birds under dynamic conditions. The methodology employed integrates raw radar data preprocessing, visualization techniques, and the development of robust bird detection and tracking algorithms. Notably, incorporating the Observation-Centric SORT (OC-SORT) algorithm for multi-bird tracking and enhanced radar data processing techniques markedly improves the system detection and tracking precision and efficiency. The effectiveness of the proposed technique is quantified evaluated through case studies in various wind farm environments. Performance metrics such as track velocity, angular trajectory changes, track duration, and quality assessment scores affirm the system superiority over Birdtrack\textsuperscript{\textregistered}. The results demonstrate a significant advancement in tracking accuracy, reduced track fragmentation, and increased detection reliability. The work in this thesis contributes to the improved operation of wind farm systems, while benefiting avian conservation. It addresses the challenges of radar-based bird monitoring and sets a foundation for future research. The successful enhancement of the Birdtrack\textsuperscript{\textregistered} system represents a crucial step in mitigating the environmental impact of wind energy operations, thus aligning sustainable energy production with ecological preservation objectives.
2022
Eco-Friendly Wind Energy: Improving Radar Tracking Systems for Bird Monitoring
The escalating global shift towards sustainable energy sources, particularly wind energy, has accentuated the need for effective measures to mitigate avian fatalities due to the operation of wind turbines. This thesis addresses this pressing ecological issue by enhancing bird tracking in radar systems - a case study on the Birdtrack\textsuperscript{\textregistered} radar system, used in wind farms for avian monitoring and collision prevention. The research presents a novel intersection of technology and ecology, significantly contributing to sustainable energy and wildlife conservation efforts. Central to this research is identifying the existing limitations of the currently adopted Birdtrack\textsuperscript{\textregistered} system in differentiating birds from environmental clutter and accurately tracking multiple birds under dynamic conditions. The methodology employed integrates raw radar data preprocessing, visualization techniques, and the development of robust bird detection and tracking algorithms. Notably, incorporating the Observation-Centric SORT (OC-SORT) algorithm for multi-bird tracking and enhanced radar data processing techniques markedly improves the system detection and tracking precision and efficiency. The effectiveness of the proposed technique is quantified evaluated through case studies in various wind farm environments. Performance metrics such as track velocity, angular trajectory changes, track duration, and quality assessment scores affirm the system superiority over Birdtrack\textsuperscript{\textregistered}. The results demonstrate a significant advancement in tracking accuracy, reduced track fragmentation, and increased detection reliability. The work in this thesis contributes to the improved operation of wind farm systems, while benefiting avian conservation. It addresses the challenges of radar-based bird monitoring and sets a foundation for future research. The successful enhancement of the Birdtrack\textsuperscript{\textregistered} system represents a crucial step in mitigating the environmental impact of wind energy operations, thus aligning sustainable energy production with ecological preservation objectives.
Radar Technology
Bird Conservation
Data Management
Clutter Reduction
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/61395