| Summary: | The passive localization of false killer whales (Pseudorca crassidens) in acoustic environments comprised of discontinuous ambient, anthropogenic, and animal sounds is a challenging problem. A background noise reduction technique is required to improve the quality of sampled recordings, which will assist localization using auditory modeling and signal correlation at extended ranges. The algorithm developed meets this requirement using a combination of adaptive percentile estimation, a median-based tracker, and Gaussian windowing. The results indicate successful improvement of the signal-to-noise ratio, and consequently a significant increase in the detection range of false killer whales in acoustically complex environments.
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