Knowledge-Guided Test and Evaluation Frameworks for proliferated Low Earth Orbit Constellations

Objective: The United States Space Force, through the Space Development Agency (SDA), seeks to develop an adaptive, knowledge-guided test-planning capability to serve as a decision aid in support of Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). PWSA is a continuously evolving constellation in Low Earth Orbit (LEO) designed to deliver resilient, threat-responsive capabilities to the joint force. Given the rapid, tranche-based deployment of capabilities under SDA’s spiral development model, traditional compliance-based test strategies are insufficient. This effort aims to prototype a modern test framework that can: - Continuously update understanding of system performance using real-time test data - Quantify expected knowledge gain relative to resource cost for each test - Dynamically re-plan test sequences to prioritize high-utility activities and truncate low-value ones The solution should incorporate probabilistic reasoning (e.g., Bayesian inference), integration of synthetic and live test data, and multi-objective utility models aligned with mission priorities (e.g., latency, resiliency, throughput). It should also support open APIs and modular architecture to ensure compatibility with SDA's digital infrastructure. Ultimately, this capability will enable smarter, faster, and more resource-efficient test campaigns that support the operational agility of the PWSA and its expanding mission scope. Description: The United States Space Force, through the Space Development Agency (SDA), is responsible for orchestrating the development and fielding of the Department of Defense’s Proliferated Warfighter Space Architecture (PWSA)—a resilient, threat-driven constellation of sensing and data transport satellites in Low Earth Orbit (LEO). Built on a spiral development model, PWSA is deployed in two-year tranches, requiring a flexible and adaptive approach to Test and Evaluation (T&E) that aligns with rapid acquisition timelines and continuous operational deployment. This topic seeks innovative solutions that adapt and extend test planning frameworks to support dynamic T&E activities for proliferated LEO architectures like PWSA. Solutions of interest should leverage knowledge-guided, sequential test planning methods capable of: - Continuously updating knowledge of system performance as test outcomes are collected - Quantifying the expected knowledge gain relative to test cost or resource usage - Dynamically re-planning test sequences to focus on high-value activities while truncating low-yield or redundant tests Of particular interest are solutions incorporating Bayesian probability theory to integrate priors, synthetic data, and live test results into an evolving, uncertainty-aware knowledge base that informs future test selections. The intent is to enable smarter and more agile test planning that can prioritize the most impactful test actions based on evolving system knowledge and operational priorities. Proposed solutions should demonstrate clear applicability to the unique demands of SDA's rapid and iterative space acquisition model and facilitate integration into evolving digital infrastructure for space system development and validation. Keywords: SDA; Space Development Agency; PWSA; pLEO; Bayesian inference; Sequential testing; Adaptive T&E; Decision support; Utility analysis; LEO constellation; Knowledge management