Multichannel models for the estimation of radon background in airborne gamma ray spectrometry

Adequate background correction is a crucial step in processing airborne gamma-ray spectrometric data because any errors are amplified during subsequent processing procedures. Two multichannel models for the estimation of atmospheric radon background are proposed. The spectral-ratio method uses the relative heights of uranium (U) series photopeaks to estimate the contribution of atmospheric radon to observed spec-tra. The full-spectrum method estimates the atmospheric radon contribution through the weighted least-squares fitting of potassium (K), U, thorium (Th), and radon component spectra to the observed spectra. Both the spectral-ratio and full-spectrum methods are adequately calibrated through the estimation of component spectra from calibration experiments on the ground using ra