Lockheed-Martin Space Operations
NASA/Goddard Space Flight Center
Greenbelt, MD 20771
The traffic management system to date relies on the available infrastructure for the collection, transmission and processing of traffic data. The technology in this field has not kept up with the state of the art due to lack of funding, lack of interest from the private sector and the lack of synergy between the various users of technology. On the other hand great strides have been made in the processing of traffic data to obtain dynamic solutions to relieve congestion, predict traffic flows and thwart threatening traffic jams. Academia and industry have been developing algorithms and models that run on traditional Central Processing Unit (CPU)-based machines to provide solutions. The delay in getting the data to the processing elements and the solution thereof have led to dynamic solutions but non-real-time implementations.
Field programmable devices are being used to address many CPU intensive bottlenecks in the space science data processing arena. Given that the interval between successive down-links is only about 90 minutes at best case, the ground processing systems have to ingest the transmitted data, process it and provide the user with usable information in this time period. The receipt of this information will enable the user to repeat, correct or disseminate the data received from space before the next data downlink. This paper will discuss a risk-averse solution to develop a system whereby the data is ingested and processed in near-real time to provide the optimal solutions for traffic management. The selection of the system elements and the allocation of the processing between hardware and the traditional processing elements will be visited and the framework for the decision process developed. The paper will outline a simple risk management process to ingest and decipher a traffic data pattern and qualitatively compare the turn around time with current technology.