Maximum cross correlation automatic satellite image navigation and attitude corrections for open-ocean image navigation

To enable "automated" image navigation (without human intervention) a base image is defined, and the maximum cross correlation (MCC) method is used to automatically compute the satellite attitude parameters required to geometrically correct images to this base image. Several levels of filters insure that contamination from cloudy pixels is minimized. The MCC method produces displacement vectors, which are translated into satellite attitude corrections to be added to the orbital image navigation corrections. The auto attitude corrections are shown to be more accurate than the traditional linear translation methods. A further application of the attitude corrections is demonstrated whereby attitude corrections computed over land can be carried forward in the satellite\´s orbit to accurately navigate imagery over the open ocean where no map reference points are available. Tested for two land sites well separated in a single orbit this method is shown to be as accurate as when applied to an individual image.