Space Object Identification using a Physically Constrained Iterative Deconvolution Algorithm

Abstract

A physically constrained iterative deconvolution algorithm is applied to both simulated and real artificial satellite (space object) observations obtained with adaptive optical systems. The problems associated with obtaining good point spread function information is discussed and the algorithm applied also permits reconstruction of not only the object but also the corresponding point spread functions.