arXiv2016
Passive imaging refers to problems where waves generated by unknown sources are recorded and used to image the medium through which they travel. The sources are typically modelled as a random variable and it is assumed that some statistical information is available. In this paper we study the stochastic wave equation $\partial_t^2 u - Δ_g u = χW$, where $W$ is a random variable with the white noise statistics on ${\mathbb R}^{1+n}$, $n \ge 3$, $χ$ is a smooth function vanishing for negative times and outside a compact set in space, and $Δ_g$ is the Laplace-Beltrami operator associated to a smooth non-trapping Riemannian metric tensor $g$ on ${\mathbb R}^n$. The metric tensor $g$ models the medium to be imaged, and we assume that it coincides with the Euclidean metric outside a compact set. We consider the empirical correlations on an open set $\mathcal X \subset {\mathbb R}^n$, $$ C_T(t_1, x_1, t_2, x_2) = \frac 1 T \int_0^T u(t_1+s,x_1) u(t_2+s,x_2) ds, \quad t_1,t_2>0,\ x_1,x_2\in \mathcal X, $$ for $T>0$. Supposing that $χ$ is non-zero on $\mathcal X$ and constant in time after $t > 1$, we show that in the limit $T \to \infty$, the data $C_T$ becomes statistically stable, that is, independent of the realization of $W$. Our main result is that, with probability one, this limit determines the Riemannian manifold $({\mathbb R}^n,g)$ up to an isometry. To our knowledge, this is the first result showing that a medium can be determined in a passive imaging setting, without assuming a separation of scales.