  In this paper, we extended our earlier work on the reconstruction of the
(time-averaged) one-dimensional velocity distribution of Galactic Weakly
Interacting Massive Particles (WIMPs) and introduce the Bayesian fitting
procedure to the theoretically predicted velocity distribution functions. In
this reconstruction process, the (rough) velocity distribution reconstructed by
using raw data from direct Dark Matter detection experiments directly, i.e.
measured recoil energies, with one or more different target materials, has been
used as "reconstructed-input" information. By assuming a fitting velocity
distribution function and scanning the parameter space based on the Bayesian
analysis, the astronomical characteristic parameters, e.g. the Solar and
Earth's Galactic velocities, will be pinned down as the output results.
  Our Monte-Carlo simulations show that this Bayesian scanning procedure could
reconstruct the true (input) WIMP velocity distribution function pretty
precisely with negligible systematic deviations of the reconstructed
characteristic Solar and Earth's velocities and 1 sigma statistical
uncertainties of <~ 20 km/s. Moreover, for the use of an improper fitting
velocity distribution function, our reconstruction process could still offer
useful information about the shape of the velocity distribution. In addition,
by comparing these estimates to theoretical predictions, one could distinguish
different (basic) functional forms of the theoretically predicted
one-dimensional WIMP velocity distribution function with 2 sigma to 4 sigma
confidence levels.
