Project Description: 

COSPAS-SARSAT is a satellite system designed to provide distress alert and location data to assist search and rescue (SAR) operations, using spacecraft and ground facilities to detect and locate the signals of distress beacons operating on 406 MHz or 121.5 Mhz bands. The position of the distress and other related information is forwarded to the appropriate Search and Rescue Point of Contact (SPOC) through the COSPAS-SARSAT Mission Control Center network. The goal of the system is to support all organizations in the world with responsibility for SAR operations, whether at sea, in the air, or on land. Operational use of COSPAS-SARSAT by SAR Agencies started with the crash of a light aircraft in Canada, in which three people were rescued (September 10, 1982). Since then, the system has been used for thousands of SAR events and has been instrumental in the rescue of over 15,000 lives worldwide.

I was assigned to work in the Systems Evaluation and Development Laboratory (SEDL) segment of the COSPAS-SARSAT program, located at the Goddard Space Flight system in Greenbelt, Maryland. The main responsibilities of this segment of the program involve post launch testing and equipment verification of newly launched NOAA spacecraft that carry the SARSAT instruments, as well as further simulation and testing of in service equipment. My main project during this period has been the development of a
software package designed to use standard NORAD Two Line Element Sets (TLEs) to calculate and propagate satellite orbital data, and provide necessary information in order to track the passage and progress of the satellite from the ground, while beginning the necessary signal analysis required to process the SAR data from the satellite. This process requires use for the NORAD SGP4 and SDP4 orbital perturbation models, both fairly involved continuations of the standard Keplerian continuous orbital model.

The ultimate goal for this project is to successfully build a software environment that can predict apparent orbital position to a high degree of accuracy when compared to the older systems currently in sue in the lab, or as much as can be expected when the two are using different element sets to generate predictions.