Arrival Estimation

Arrival estimation focuses on determining the origin or direction of signals, crucial for diverse applications ranging from robotics and autonomous vehicles to speech processing and fire modeling. Current research emphasizes improving accuracy and robustness in challenging environments (noise, reverberation, clutter) using advanced algorithms like those based on deep learning (e.g., transformers, convolutional neural networks), sparse array processing, and optimal transport formulations, often incorporating reliability weighting or feedback mechanisms. These advancements are significant for enhancing the performance of various systems that rely on accurate signal localization, improving safety, efficiency, and user experience across multiple domains.