You cannot effectively defend yourself if you don’t know what you’re up against. At SGT, we are recognized experts in the critical field of Space Situational Awareness (SSA). Our experts provide essential software engineering, systems engineering, enterprise architectures, modeling and simulation (M&S), and lifecycle logistics support to the Space Surveillance Network and various Command, Control, Communication, and Computer, Intelligence, Surveillance, and Reconnaissance (C4ISR) systems and programs. Our radar experience includes supporting the Eglin AN/FPS-85 Phased Array Space Surveillance Radar, Perimeter Acquisition Radar Attack Characterization System (PARCS), HAVE STARE, COBRA DANE, Ballistic Missile Early Warning System (BMEWS), and PAVE Phased Array Warning Systems (PAWS), radar systems supporting space surveillance, missile warning, and intelligence gathering mission areas. As a result, SGT’s scientists help establish unparalleled reconnaissance and surveillance from the vantage point of space.
- Mission systems software development
- Development processes
- Software tool development
- Architecture-based development
- Algorithm development
- Mission planning
- Target discrimination
- Tracking filters
- Digital signal processing
- Leading edge technology
Specific areas of expertise relative to SSA efforts include the following:
Space Surveillance Network Analysis Model (SSNAM) — Our personnel have supported the development and maintenance of SSNAM, an AFSPC modeling and simulation tool to simulate the current SSN and proposed changes. SSNAM is a decision support system (DSS) used to evaluate a variety of what-if scenarios for such programs as NAVSPASUR, MSX/SATA, and the Space-Based Surveillance System (SBSS). It provides an initial analysis model for end-to-end simulations, reenactments, and studies of space surveillance missions and events to quantify SSN performance, response, and processing characteristics. SSNAM allows decision-makers to understand the impact of changes in SSN capabilities to the quality of the space object catalog. SSNAM analyzes changes in tasking, sensor schedules, sensor capabilities, catalog size, (e.g., anticipating Space Fence), and introduces new characteristics (e.g., debris cloud) to understand their impact on sensor performance
Event Based Processing including Breakup Detection — SGT combined automated processing with operator-in-the-loop to analyze real-time events including breakup detection to provide real-time awareness of events by the operators. This capability provides rapid threat assessment in support for Space Situational Awareness.