New Sensing Strategies for Estimation of Global, Exospheric Density

Abstract

AbstractReliable quantification of the global and time‐dependent structure of the Earth's outermost atmosphere, a vast region known as the exosphere, has long been elusive, owing mainly to the sparse spatial and temporal sampling afforded by exospheric sensing platforms deployed to date. In this paper, we introduce new observing schemes that overcome these historical limitations and enable high‐fidelity, high‐cadence reconstruction of the exospheric density distribution on a global scale. Our approach leverages several state‐of‐the‐art remote sensing capabilities, including (1) wide‐field photometric imaging of exospheric emission, which is created through resonant photon scattering by the exosphere's constituent hydrogen atoms; (2) constellation sensor deployment near lunar orbit, which provides common‐volume sensing; and (3) tomographic inversion of a discretized exospheric emission model that explicitly accounts for the Poisson‐distributed shot noise inherent in the photometric data constraints. Using ensembles of synthetic emission data acquired at various realistic temporal cadences, we evaluate the fidelity of both static density reconstructions, in which the solution is formulated in the context of maximum a posteriori (MAP) estimation, as well as dynamic density reconstructions, which incorporate temporal evolution via Kalman filtering. The numerical results demonstrate that the new sensing strategies are capable of retrieving reliable estimates of exospheric density distribution at unprecedented spatial scales and temporal cadence, in support of numerous high‐priority investigations of Earth's near‐space environment.