Gilles Chardon (L2S)

Localisation et imagerie acoustiques

Resume (assisted by AI): This presentation is about acoustic source localization and imaging with microphone arrays, covering both theory and advanced algorithms. It introduces the problem and classical source-localization applications, then explains beamforming—highlighting steering-vector choices, bias/variance behavior, and limits in resolution. It then presents DAMAS and Covariance Matrix Fitting (CMF), clarifying convergence properties and offering faster implementations, along with comparisons to CLEAN-type methods. The talk also explores gridless approaches such as BLASSO and Sliding Frank–Wolfe for super-resolution imaging, as well as extensions to correlated sources with greedy algorithms and asynchronous arrays analyzed using maximum-likelihood estimation and Cramér–Rao bounds. Throughout, simulated and experimental results (2D and 3D) demonstrate performance, robustness at low SNR, and computational considerations.