  To reach its optimal performance, Fizeau interferometry requires that we work
to resolve instrumental biases through calibration. One common technique used
in high contrast imaging is angular differential imaging, which calibrates the
point spread function and flux leakage using a rotation in the focal plane.
  Our aim is to experimentally demonstrate and validate the efficacy of an
angular differential kernel-phase approach, a new method for self-calibrating
interferometric observables that operates similarly to angular differential
imaging, while retaining their statistical properties.
  We used linear algebra to construct new observables that evolve outside of
the subspace spanned by static biases. On-sky observations of a binary star
with the SCExAO instrument at the Subaru telescope were used to demonstrate the
practicality of this technique. We used a classical approach on the same data
to compare the effectiveness of this method.
  The proposed method shows smaller and more Gaussian residuals compared to
classical calibration methods, while retaining compatibility with the
statistical tools available. We also provide a measurement of the stability of
the SCExAO instrument that is relevant to the application of the technique.
  Angular differential kernel phases provide a reliable method for calibrating
biased observables. Although the sensitivity at small separations is reduced
for small field rotations, the calibration is effectively improved and the
number of subjective choices is reduced.
