Eigenvector Sky Subtraction
  We develop a new method for estimating and removing the spectrum of the sky from deep spectroscopic observations; our method does not rely on simultaneous measurement of the sky spectrum with the object spectrum. The technique is based on the iterative subtraction of continuum estimates and Eigenvector sky models derived from Singular Value Decompositions (SVD) of sky spectra, and sky spectra residuals. Using simulated data derived from small telescope observations we demonstrate that the method is effective for faint objects on large telescopes. We discuss simple methods to combine our new technique with the simultaneous measurement of sky to obtain sky subtraction very near the Poisson limit. 
Michael J. Kurtz and Douglas J. Mink