Track Store Synchronization Using Semantic Models for AEGIS Combat System

This proposal addresses the Navy's requirement for automated track synchronization across the AEGIS Combat System (ACS). The current architecture, where multiple source managers maintain local track stores alongside the Joint Track Manager (JTM), can experience synchronization issues due to race conditions in data processing and concurrent updates. These inconsistencies can degrade situational awareness and impact combat system effectiveness.RTI proposes a non-intrusive solution that leverages data-centric modeling capabilities. The key innovation of our approach is the use of semantic models to capture complex relationships between track attributes and understand the specialized roles of different track sources. These models enable intelligent comparison and correction strategies that account for partial track data sets and normal fusion-related variations. By understanding the semantic meaning of track data, our system can better distinguish between expected temporary inconsistencies and true synchronization problems that require correction.The Phase I effort will focus on concept development and risk reduction through detailed requirements analysis and technology exploration. We will create a test environment to reproduce synchronization issues and evaluate different detection strategies. Working with stakeholders, we will identify representative use cases that demonstrate both technical challenges and operational impact. Our investigation will explore semantic modeling approaches that enable sophisticated track correlation while maintaining DDS performance characteristics.RTI brings extensive DDS expertise, proven monitoring capabilities, and established relationships with AEGIS stakeholders. If funded through Phase II, this effort will deliver a prototype that enhances AEGIS track management reliability while providing a foundation for broader adoption across Navy combat systems.