  Differentiating between an exoplanet signal and residual speckle noise is a
key challenge in high-contrast imaging. Speckles are due to a combination of
fast, slow and static wavefront aberrations introduced by atmospheric
turbulence and instrument optics. While wavefront control techniques developed
over the last decade have shown promise in minimizing fast atmospheric
residuals, slow and static aberrations such as non-common path aberrations
(NCPAs) remain a key limiting factor for exoplanet detection. NCPA are not seen
by the wavefront sensor (WFS) of the adaptive optics (AO) loop, hence the
difficulty in correcting them. We propose to improve the identification and
rejection of those aberrations. The algorithm DrWHO, performs frequent
compensation of static and quasi-static aberrations to boost image contrast. By
changing the WFS reference at every iteration of the algorithm, DrWHO changes
the AO point of convergence to lead it towards a compensation of the static and
slow aberrations. References are calculated using an iterative lucky-imaging
approach, where each iteration updates the WFS reference, ultimately favoring
high-quality focal plane images. We validate this concept through numerical
simulations and on-sky testing on the SCExAO instrument at the 8.2-m Subaru
telescope. Simulations show a rapid convergence towards the correction of 82%
of the NCPAs. On-sky tests are performed over a 10-minute run in the visible
(750 nm). We introduce a flux concentration (FC) metric to quantify the point
spread function (PSF) quality and measure a 15.7% improvement. The DrWHO
algorithm is a robust focal-plane wavefront sensing calibration method that has
been successfully demonstrated on sky. It does not rely on a model nor requires
wavefront sensor calibration or linearity. It is compatible with different
wavefront control methods, and can be further optimized for speed and
efficiency.
