  We developed a method to infer the calibration parameters of multichannel
measurement systems, such as channel variations of sensitivity and noise
amplitude, from experimental data. We regard such uncertainties of the
calibration parameters as dependent noise. The statistical properties of the
dependent noise and that of the latent functions were modeled and implemented
in the Gaussian process kernel. Based on their statistical difference, both
parameters were inferred from the data.
  We applied this method to the electron density measurement system by Thomson
scattering for Large Helical Device plasma, which is equipped with 141 spatial
channels. Based on the 210 sets of experimental data, we evaluated the
correction factor of the sensitivity and noise amplitude for each channel. The
correction factor varies by $\approx$ 10\%, and the random noise amplitude is
$\approx$ 2\%, i.e., the measurement accuracy increases by a factor of 5 after
this sensitivity correction. The certainty improvement in the spatial
derivative inference was demonstrated.
