AN ADVANCED OPTIMAL SPECTRAL ESTIMATION ALGORITHM IN FOURIER SPECTROSCOPY WITH APPLICATION TO REMOTE-SENSING OF THE ATMOSPHERE

Remote sensing of the atmosphere from satellite to improve numerical w eather prediction demands objective data handling methods, as the effe ctiveness of satellite data ultimately rests on our ability to process the data in real time. In this paper a procedure to recover high-reso lution spectra from infrared Fourier spectrometer data is presented. T he technique relies on the generalized cross-validation criterion and retains all the computational characteristics that are proper to the f ast Fourier transform. The procedure yields adaptive apodizing functio ns that improve the convergence of the Fourier transform. Numerical ex amples are carried out using synthetic spectra computed by a high-reso lution radiative transfer code. The effect of additive noise is also a nalyzed. The application of the technique to remote sensing of the atm osphere is discussed. Although our applications of the method emphasiz e the problem of recovering radiance spectra from interferogram signal s. the procedure also applies in a general context, for example, to th e estimation of variance spectra of stochastic processes from their au tocovariance functions.