  In this paper, quantitative bounds in high-frequency central limit theorems
are derived for Poisson based $U$-statistics of arbitrary degree built by means
of wavelet coefficients over compact Riemannian manifolds. The wavelets
considered here are the so-called needlets, characterized by strong
concentration properties and by an exact reconstruction formula. Furthermore,
we consider Poisson point processes over the manifold such that the density
function associated to its control measure lives in a Besov space. The main
findings of this paper include new rates of convergence that depend strongly on
the degree of regularity of the control measure of the underlying Poisson point
process, providing a refined understanding of the connection between regularity
and speed of convergence in this framework.
