Robust Ocean Acoustic Localization With Sparse Bayesian Learning
Matched field processing (MFP) compares the measures to the modeled pressure fields received at an array of sensors to localize a source in an ocean…
Read moreJSTSP Volume 13 Issue 1
Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained With Noise Signals
Supervised learning-based methods for source localization, being data driven, can be adapted to different acoustic conditions via training and have…
Read moreSparse Representation of a Spatial Sound Field in a Reverberant Environment
This paper investigates sound-field modeling in a realistic reverberant setting. Starting from a few point-like microphone measurements, the goal is…
Read moreIntroduction to the Issue on Acoustic Source Localization and Tracking in Dynamic Real-Life Scenes
Acoustic source localization and tracking is a well-studied topic in signal processing, but most traditional methods incorporate simplifying…
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