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Acoustic Detection, Source Separation, And Classification Algorithms For Unmanned Aerial Vehicles In Wildlife Monitoring And Poaching, Carlo Lopez-Tello
Acoustic Detection, Source Separation, And Classification Algorithms For Unmanned Aerial Vehicles In Wildlife Monitoring And Poaching, Carlo Lopez-Tello
UNLV Theses, Dissertations, Professional Papers, and Capstones
This work focuses on the problem of acoustic detection, source separation, and classification under noisy conditions. The goal of this work is to develop a system that is able to detect poachers and animals in the wild by using microphones mounted on unmanned aerial vehicles (UAVs). The classes of signals used to detect wildlife and poachers include: mammals, birds, vehicles and firearms. The noise signals under consideration include: colored noises, UAV propeller and wind noises.
The system consists of three sub-systems: source separation (SS), signal detection, and signal classification. Non-negative Matrix Factorization (NMF) is used for source separation, and random …