Geometric Radar Processing based on Fréchet distance: Information geometry versus Optimal Transport Theory

摘要

In the framework of Optimal Transport Theory, Fréchet-Wasserstein distance could be used to define distance for signal radar measures modeled by multivariate Gaussian laws with positive curvature geometry. We compare this approach with Information geometry for Covariance Radar Matrices Processing, where Fisher metric and Siegel-Rao distance provides geometry of negative curvature.