A strategy is needed for a regional survey of geosynchronous orbits (GSOs) to monitor known space objects and detect uncataloged space objects. On the basis of the Inter-Agency Debris Committee’s recommendation regarding the protected region of geosynchronous Earth orbit (GEO), target satellites with perigee and apogee of GEO ± 200 km and various inclinations are selected for analysis. The status of the GSO region was analyzed using the satellite distribution based on the orbital characteristics in publicly available two-line element data. Natural perturbation effects cause inactive satellites to drift to two stable longitudinal points. Active satellites usually maintain the designed positions as a result of regular or irregular maneuver operations against their natural drift. To analyze the detection rate of a single optical telescope, 152 out of 412 active satellites and 135 out of 288 inactive satellites in the GSO region were selected on the basis of their visibility at the observation site in Daejeon, Korea. By using various vertical view ranges and various numbers of observations of the GSO region, the detection efficiencies were analyzed for a single night, and the numbers of follow-up observations were determined. The orbital estimation accuracies were also checked using the arc length and number of observed data points to maintain the GSO satellite catalog.

An algorithm to automatically extract coordinate and time information from optical observation data of geostationary orbit satellites (GEO satellites) or geosynchronous orbit satellites (GOS satellites) is developed. The optical wide-field patrol system is capable of automatic observation using a pre-arranged schedule. Therefore, if this type of automatic analysis algorithm is available, daily unmanned monitoring of GEO satellites can be possible. For data acquisition for development, the COMS1 satellite was observed with 1-s exposure time and 1-m interval. The images were grouped and processed in terms of “action”, and each action was composed of six or nine successive images. First, a reference image with the best quality in one action was selected. Next, the rest of the images in the action were geometrically transformed to fit in the horizontal coordinate system (expressed in azimuthal angle and elevation) of the reference image. Then, these images were median-combined to retain only the possible non-moving GEO candidates. By reverting the coordinate transformation of the positions of these GEO satellite candidates, the final coordinates could be calculated.