  Knowledge of the atmospheric turbulence in the telescope line-of-sight is
crucial for wide-field observations assisted by adaptive optics (AO), for which
the Point Spread Function (PSF) becomes strongly elongated due to the
anisoplanatism effect. This one must be modelled accurately to extrapolate the
PSF anywhere across the Field of view (FOV) and improve the science
exploitation. However, anisoplanatism is a function of the Cn2(h) profile, that
is not directly accessible from single conjugate AO telemetry. One may rely on
external profilers, but recent studies have highlighted more than 10% of
discrepancies with AO internal measurements, while we aim better than 1% of
accuracy for PSF modelling. To tackle this existing limitation, we present the
Focal plane profiling (FPP), as a $C_n^2(h)$ profiling method that relies on
post-AO focal plane images. We demonstrate such an approach complies with a
1%-level of accuracy on the $C_n^2(h)$ estimation and establish how this
accuracy varies regarding the calibration stars magnitudes and positions in the
field. We highlight that photometry and astrometry errors due to PSF
mis-modelling reaches respectively 1% and 50{\mu}as using FPP on a Keck
baseline, with a preliminary calibration using a star of magnitude H=14 at 20".
We also validate this concept using Canadas NRC-Herzberg HENOS testbed images
in comparing FPP retrieval with alternative $C_n^2(h)$ measurements on HeNOS.
The FPP approach allows to profile the $C_n^2(h)$ using the SCAO systems and
improve significantly the PSF characterisation. Such a methodology is also
ELT-size compliant and will be extrapolated to tomographic systems in a near
future.
