Applications of random matrix theory for sensor array imaging with measurement noise

Josselin Garnier (1, 2) , Knut Solna (3)

1 LJLL - Laboratoire Jacques-Louis Lions
2 LPMA - Laboratoire de Probabilités et Modèles Aléatoires
3 Department of Mathematics [Irvine]

The imaging of a small target embedded in a medium is a central problem in sensor array imaging. The goal is to find a target embedded in a medium. The medium is probed by an array of sources, and the signals backscattered by the target are recorded by an array of receivers. The responses between all pairs of source and receiver are collected so that the available information takes the form of a response matrix. When the data are corrupted by additive measurement noise we show how tools of random matrix theory can help to detect, localize, and characterize the target.

Mots clés: random matrix theory

Domaines: Probabilités [math.PR]; Equations aux dérivées partielles [math.AP]

Josselin Garnier, Knut Solna. Applications of random matrix theory for sensor array imaging with measurement noise. P. Deift, P. Forrester. Random Matrix Theory, Interacting Particle Systems, and Integrable Systems, Cambridge University Press, pp.223-246, 2014. ⟨hal-01108858⟩