Large-scale simulation of bird localization systems in forests with distributed microphone arrays

Area of Science:

• Ecology
• Bioacoustics
• Signal Processing

Background:

• Acoustic wildlife monitoring is vital for ecosystem habitation studies.
• Audio-based bird localization is effective, but performance in large forests is understudied.
• Distributed microphone arrays offer potential for large-scale monitoring.

Purpose of the Study:

• To evaluate the performance and robustness of distributed microphone arrays for bird localization in simulated forest environments.
• To identify key factors influencing localization accuracy in realistic acoustic conditions.

Main Methods:

• Simulated forest scenes incorporating reverberation, ambient noise, and measurement errors.
• Analysis of bird localization algorithms using distributed microphone arrays.
• Investigation of signal-to-noise ratio and spectral weighting effects.

Main Results:

• Localization accuracy is significantly influenced by the signal-to-noise ratio.
• Spectral weighting in the localization algorithm plays a critical role in performance.
• Simulations highlight challenges of distributed systems in reverberant and noisy forest settings.

Conclusions:

• Signal-to-noise ratio and spectral weighting are critical parameters for effective bird localization in forests.
• The findings provide guidance for designing robust, large-scale acoustic wildlife monitoring systems.
• Further research should focus on improving algorithms for challenging acoustic environments.