International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / The next-generation commercial imaging satellites will generate data at several times the rate of current systems. To be commercially successful, these systems must have earth stations as sophisticated as the satellites themselves. Space Imaging has worked with E-Systems to exploit technologies developed over four generations of image processing, analysis and application systems to create a modular, standards-based, earth station for commercial use. A Space Imaging Operations Center can be configured in a variety of ways to provide complete, end-to-end, capabilities, from task generation to receipt of downlink, image processing, and product generation. While it is intended primarily for use with imagery from Space Imaging and other commercial satellites, an Operations Center can also accept, process and manage data from land-based, airborne or seaborne collectors. A sophisticated data management product, Mission Server™, handles and routes all data from signal receipt through final product generation. A unique family of data processing applications permit simultaneous manipulation and analysis of integrated map, image, graphic and text data. Online data storage and archiving are provided by the EMASS® family of products. An Operations Center of any size can accept, process and manage data streams of several hundred megabits per second in real time.

In the world of educational satellites, student teams manually conduct operations daily, sending commands and collecting downlinked data. Educational satellites typically travel in a Low Earth Orbit allowing line of sight communication for approximately thirty minutes each day. This is manageable for student teams as the required manpower is minimal. The international Global Educational Network for Satellite Operations (GENSO), however, promises satellite contact upwards of sixteen hours per day by connecting earth stations all over the world through the Internet. This dramatic increase in satellite communication time is unreasonable for student teams to conduct manual operations and alternatives must be explored. This thesis first introduces a framework for developing different Artificial Intelligences to conduct autonomous satellite operations for CubeSat satellites. Three different implementations are then compared using Cal Poly's CP6 CubeSat and the University of Tokyo's XI-IV CubeSat to determine which method is most effective.