Battle Damage Indications / Battle Damage Assessment Collection, Aggregation, and Analytics Improvement

To preserve decision advantage during contested-space operations, the United States Space Force (USSF) must rapidly correlate multi-source operational data to streamline Phase 5 (Mission Planning & Force Execution) and Phase 6 (Assessment) of the Space Tasking Cycle (STC) and Joint Targeting Cycle (JTC). The Space Systems Command (SSC) System Delta 85 (SYD 85) Program Management Office (PMO) and the Kronos Program of Record (PoR), in support of the Battle Management, Command, Control, Communications, and Space Intelligence Portfolio Acquisition Executive (BMC3I PAE), is seeking software-based solutions for the BMC3I TAP Lab (Tools, Applications, & Processing) to automate, aggregate, and score multi-phenomenology collection activities in a standardized, Unclassified environment designed for the eventual seamless scaling to classified operational networks. Within this request, there are 5 associated subtasks: 1. Automated ingestion and schema mapping of multiple heterogeneous sensor and telemetry sources telemetry and sensor sources into a common BDI/A data store Ontology definition model while preserving metadata and timestamp traceability; 2. Cross-domain synchronization and analytics of Electro-Optical/Infra-Red (EO/IR), Radio Frequency (RF), and Radar data products (such as resolved/unresolved observations, Doppler Residuals, and Area-to-Mass Ratio datasets) to detect pre-defined anomalous behaviors using configurable threat signatures; 3. Execution of a dynamic, multi-phenomenology confidence scoring framework that evaluates collection source reliability and sensor quality metrics; 4. Development of user-friendly, explainable AI/ML-assisted correlation diagnostics that expose the underlying analytical rationale to human operators to assist in target adjudication; and 5. Delivery of a segmented user interface enabling Subject Matter Experts (SMEs) to isolate and execute workflows across the four distinct echelons of the BDI/A lifecycle (Tactical BDI, BDA Phase 1, BDA Phase 2, and BDA Phase 3). Sample inputs include; - Real-time or historical feeds; - Ground- and space-based multi-phenomenology sensor data (commercial and government); - Historical event repositories for change detection; and - Simulated operational event logs. Possible techniques may include but are not limited to; - Automated schema mapping and metadata parsing; - Change detection algorithms against historical patterns of life; - Multi-hypothesis data association and Kalman filtering; and - Explainable AI (XAI) natural language explanation generation. The software product must be designed to integrate with existing and legacy Mission Unique Software (MUS) toolchains, publishing assessments back to source repositories via standardized application programming interfaces (APIs) and meeting all development requirements for future transition to secure operational networks.