Generalized Information Network Analysis

GINA – Conceptual Design of Distributed Satellite Systems

GINA - the Generalized Information Network Analysis methodology for Distributed Satellite Systems (DSS) - is a systems engineering and architecting (SE&A) framework developed by the MIT Space Systems Laboratory for the conceptual design of space systems. GINA enables the creation and comparison of numerous different design architectures for a given mission. The foundation behind the GINA methodology is the belief that all satellite systems are information disseminators that can be represented as information transfer networks.

• Decentralized resources
  -Survivable
• Smaller, simpler satellites
  -Reduced cost & time
• Modular design
  -Upgradable
• Spatially distributed
  -Improved revisit
• Reduced range
  -Reduced power-aperture
• Separated, sparse apertures
  -Improved resolution

• Cost per Function
  -Cost per billable minute
  -Cost per useful image
• Capability
  -Resolution
  -Rate
  -Integrity
  -Availability
• Adaptability
  -Cost and performance elasticity to changes in requirements

A summary of the procedural steps in the GINA methodology is listed below.

1. Define the Mission Objective and the Conceptual Design Stage (CDS) Objective.
   • Identify the customer
   • State mission objective
   • Derive top level customer requirements
   • State CDS objective
2. Transform the Space System into an Information Network
   • Identify the origin-destination pairs in the network
   • Draw the network
   • Identify the 4 capability quality of service metrics
3. Develop System Metrics
   • Define the performance, cost per function, and adaptability metrics by which all proposed system architectures will be compared and evaluated.
4. Partition the Problem
   • Define the design vector and constants vector
   • Matrix the design vector against the capability metrics
   • Define the modules
     
     
     
     
5. Develop Simulation Software
   • Develop each module
   • Code each module
   • Integrate the coded modules
     
     
     
     
6. Explore the System Trade Space
   • Evaluate the desired architectures on the basis of the system metrics
   • Apply an optimization algorithm if desired
     
     
     
     

Conclusions

Through these steps, GINA allows the systems engineer to make meaningful, quantitative trades at the conceptual design level by directly relating lifecycle performance to lifecycle cost. Missions for which GINA has been applied to include the USAF TechSat 21 constellation, the NASA JPL Terrestrial Planet Finder interferometer, NAVSTAR GPS, and Ka-broadband telecommunications systems.