Source Localization

Source localization aims to pinpoint the origin of signals, whether sound, gas, radio waves, or information spreading through a network. Current research emphasizes developing robust algorithms, including Bayesian methods, neural networks (especially diffusion models), and graph-based approaches, to overcome challenges like noise, reverberation, and the inherent ill-posed nature of many inverse problems. These advancements are crucial for diverse applications ranging from environmental monitoring and industrial inspection to astronomy and network security, improving accuracy and efficiency in locating sources across various domains. The field is also seeing increased use of multi-modal and multi-robot systems for improved performance and robustness.