  Solar Orbiter provides dust detection capability in inner heliosphere, but
estimating physical properties of detected dust from the collected data is far
from straightforward. First, a physical model for dust collection considering a
Poisson process is formulated. Second, it is shown that dust on hyperbolic
orbits is responsible for the majority of dust detections with Solar Orbiter's
Radio and Plasma Waves (SolO/RPW). Third, the model for dust counts is fitted
to SolO/RPW data and parameters of the dust are inferred, namely: radial
velocity, hyperbolic meteoroids predominance, and solar radiation pressure to
gravity ratio as well as uncertainties of these. Non-parametric model fitting
is used to get the difference between inbound and outbound detection rate and
dust radial velocity is thus estimated. A hierarchical Bayesian model is
formulated and applied to available SolO/RPW data. The model uses the
methodology of Integrated Nested Laplace Approximation, estimating parameters
of dust and their uncertainties. SolO/RPW dust observations can be modelled as
a Poisson process in a Bayesian framework and observations up to this date are
consistent with the hyperbolic dust model with an additional background
component. Analysis suggests a radial velocity of the hyperbolic component
around $(63 \pm 7) \mathrm{km/s}$ with the predominance of hyperbolic dust
about $(78 \pm 4) \%$. The results are consistent with hyperbolic meteoroids
originating between $0.02 \mathrm{AU}$ and $0.1 \mathrm{AU}$ and showing
substantial deceleration, which implies effective solar radiation pressure to
gravity ratio $\gtrsim 0.5$. The flux of hyperbolic component at $1
\mathrm{AU}$ is found to be $(1.1 \pm 0.2) \times 10^{-4}
\mathrm{m^{-2}s^{-1}}$ and the flux of background component at $1 \mathrm{AU}$
is found to be $(5.4 \pm 1.5) \times 10^{-5} \mathrm{m^{-2}s^{-1}}$.
