Knowledge-Guided Test and Evaluation Frameworks for proliferated Low Earth Orbit Constellations
ID: SF254-D1206Type: Phase II
Overview

Topic

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

Agency

Agency: DODBranch: USAF

Program

Type: SBIRPhase: Phase II

Topic Link

https://www.dodsbirsttr.mil/topics-app/

Additional Information

https://www.dodsbirsttr.mil/topics-app/
Timeline
    Description

    The United States Space Force, through the Space Development Agency (SDA), is seeking innovative solutions for a knowledge-guided test and evaluation framework to support the Proliferated Warfighter Space Architecture (PWSA), a dynamic constellation of satellites in Low Earth Orbit (LEO). The objective is to develop an adaptive test-planning capability that continuously updates system performance using real-time data, quantifies knowledge gain relative to resource costs, and dynamically re-plans test sequences to prioritize high-utility activities, leveraging probabilistic reasoning and integrating both synthetic and live test data. This opportunity is critical for enhancing the efficiency and effectiveness of test and evaluation activities in alignment with SDA's rapid acquisition model, with proposals due by January 28, 2026. Interested parties can find more information and submit proposals through the official solicitation link provided by the Department of Defense.

    Files
    Title
    Posted
    1762382892043.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for its Proliferated Warfighter Space Architecture (PWSA), a rapidly evolving Low Earth Orbit (LEO) constellation. Traditional compliance-based testing is insufficient for PWSA's spiral development model. The objective is to prototype a modern test framework that continuously updates system performance understanding using real-time data, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities like latency and resiliency. The framework must support open APIs and modular architecture for compatibility with SDA's digital infrastructure, enabling smarter, faster, and more resource-efficient test campaigns. This effort will transition a prototype into an operational tool for adaptive, data-informed Test and Evaluation (T&E) activities across SDA's satellite constellations, with a focus on operational integration, decision support at scale, and commercialization for other pLEO operators.
    1762387306536.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for the Proliferated Warfighter Space Architecture (PWSA), a rapidly evolving Low Earth Orbit (LEO) constellation. Traditional compliance-based testing is insufficient for PWSA's spiral development model. The objective is to prototype a framework that continuously updates system performance using real-time data, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities. The solution needs open APIs and a modular architecture for compatibility with SDA's digital infrastructure, enabling smarter, faster, and more resource-efficient test campaigns. This Direct-to-Phase II effort will mature the framework, tailor it to pLEO architectures, and transition it into an operational tool for SDA and other government/commercial pLEO constellations.
    1762560123665.pdf
    The Space Development Agency (SDA) seeks innovative solutions for an adaptive, knowledge-guided test-planning capability to support Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). PWSA, a rapidly evolving Low Earth Orbit (LEO) constellation, requires a modern test framework that can continuously update system performance using real-time data, quantify knowledge gain versus resource cost, and dynamically re-plan test sequences. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities like latency and resiliency. This effort aims to enable smarter, faster, and more resource-efficient test campaigns to support PWSA's operational agility. Direct-to-Phase II proposals are required, demonstrating a feasibility study and clear integration pathways. Phase II will focus on maturing and tailoring the framework for pLEO architectures, while Phase III will transition the capability into operational use across government and commercial sectors.
    1762646519958.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability to aid Test & Evaluation (T&E) activities for its Proliferated Warfighter Space Architecture (PWSA). This Low Earth Orbit (LEO) constellation requires a modern test framework due to its rapid, tranche-based deployment. The framework must continuously update system performance using real-time data, quantify knowledge gain versus resource cost, and dynamically re-plan test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning, integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities. This Direct-to-Phase-II effort emphasizes maturing a prototype into an operational tool, adapting it to PWSA’s T&E environment, defining open APIs, and developing containerized toolkits. Phase III will focus on operational integration, scaling for decision support, commercialization, and sustainment, aiming to deliver a robust, flexible, and embedded test planning capability to enhance mission assurance and reduce validation costs for government and commercial pLEO constellations.
    1762819318920.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for its Proliferated Warfighter Space Architecture (PWSA) in Low Earth Orbit (LEO). This capability will serve as a decision aid for Test & Evaluation (T&E) activities, moving beyond traditional compliance-based strategies due to PWSA's rapid, tranche-based deployment. The objective is to continuously update system performance understanding using real-time data, quantify knowledge gain versus resource cost for each test, and dynamically re-plan test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities like latency, resiliency, and throughput. The framework must support open APIs and modular architecture for compatibility with SDA's digital infrastructure, enabling smarter, faster, and more resource-efficient test campaigns. This effort is a Direct-to-Phase II, focusing on prototyping, demonstration, and eventual operational integration into SDA's evolving satellite constellations and potentially commercial pLEO operators.
    1762905704537.pdf
    The Space Development Agency (SDA) seeks innovative solutions for an adaptive, knowledge-guided test-planning capability to support Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). This continuously evolving Low Earth Orbit (LEO) constellation requires a modern test framework that can continuously update system performance understanding using real-time data, quantify knowledge gain versus resource cost, and dynamically re-plan test sequences. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities. The goal is smarter, faster, and more resource-efficient test campaigns to support PWSA's operational agility. This is a Direct-to-Phase II effort, requiring applicants to demonstrate prior feasibility and a clear plan for integration with Department of Air Force (DAF) operations. Phase II will focus on maturing and tailoring the framework for pLEO architectures, transitioning a prototype into an operational tool. Phase III will involve operational integration, scaling decision support, commercialization, and sustainment for broader use across government and commercial space operations.
    1762992134373.pdf
    The Space Development Agency (SDA) seeks innovative solutions for an adaptive, knowledge-guided test-planning capability to support Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). This continuously evolving Low Earth Orbit (LEO) constellation requires a modern test framework capable of continuously updating system performance understanding, quantifying knowledge gain relative to resource cost, and dynamically re-planning test sequences. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and utilize multi-objective utility models aligned with mission priorities like latency, resiliency, and throughput. The objective is to enable smarter, faster, and more resource-efficient test campaigns for PWSA's operational agility. The project will not include Phase I, instead focusing on Direct-to-Phase II proposals demonstrating a feasibility study. Phase II will mature the framework into an operationally relevant tool, while Phase III aims for operational integration across government and commercial pLEO constellations, focusing on scalability, decision support, and sustainment.
    1763078529252.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for its Proliferated Warfighter Space Architecture (PWSA). This Low Earth Orbit (LEO) constellation requires a modern test framework that continuously updates system performance using real-time data, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and utilize multi-objective utility models aligned with mission priorities like latency and resiliency. This effort aims to enable smarter, faster, and more resource-efficient test campaigns to support PWSA's operational agility and expanding mission scope, moving directly into Phase II to mature and transition a prototype into an operationally relevant tool.
    1763164918053.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for the Proliferated Warfighter Space Architecture (PWSA), a rapidly evolving Low Earth Orbit (LEO) constellation. Traditional test strategies are insufficient for PWSA's spiral development model, necessitating a modern framework that continuously updates system performance understanding, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities. This Direct-to-Phase II effort focuses on maturing a prototype framework into an operational tool, integrating it with SDA's digital infrastructure, and developing use cases for demonstration and refinement. Phase III aims for operational integration across government and commercial pLEO constellations, focusing on scalability, decision support, commercialization, and sustainment to enhance mission assurance and reduce validation costs.
    1763337716292.pdf
    The Space Development Agency (SDA) seeks innovative solutions for an adaptive, knowledge-guided test-planning capability to support Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). This continuously evolving Low Earth Orbit (LEO) constellation requires a modern test framework that can continuously update system performance using real-time data, quantify knowledge gain relative to resource cost, and dynamically re-plan test sequences to prioritize high-utility activities. The solution should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities like latency and resiliency. This direct-to-Phase II effort aims to mature a prototype into an operationally relevant tool, ensuring compatibility with SDA's digital infrastructure and supporting agile space acquisition. Phase III will focus on operational integration across government and commercial pLEO constellations, expanding decision support, and establishing sustainment mechanisms.
    1763510525935.pdf
    The United States Space Force, through the Space Development Agency (SDA), is seeking proposals for an adaptive, knowledge-guided test-planning capability to support Test & Evaluation (T&E) activities for the Proliferated Warfighter Space Architecture (PWSA). This architecture comprises continuously evolving Low Earth Orbit (LEO) constellations, making traditional compliance-based test strategies insufficient. The objective is to develop a modern test framework that can continuously update understanding of system performance, quantify knowledge gain relative to resource cost, and dynamically re-plan test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and utilize multi-objective utility models aligned with mission priorities like latency and resiliency. This effort aims to enable smarter, faster, and more resource-efficient test campaigns, supporting the operational agility of the PWSA. This topic is intended for Direct-to-Phase-II proposals, requiring a demonstrated feasibility study. Phase II will focus on maturing the framework into an operationally relevant tool, while Phase III will transition it into operational use across SDA and other pLEO constellations, with commercialization potential.
    1764968596138.pdf
    The Space Development Agency (SDA) seeks an adaptive, knowledge-guided test-planning capability for the Proliferated Warfighter Space Architecture (PWSA), a rapidly evolving Low Earth Orbit (LEO) constellation. Traditional test strategies are insufficient for PWSA's spiral development model. The objective is to prototype a modern test framework that continuously updates system performance, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities like latency and resiliency. The capability must support open APIs and modular architecture, enabling smarter, faster, and more resource-efficient test campaigns. This effort is restricted under ITAR/EAR. Phase I is direct-to-Phase II, requiring a feasibility study demonstrating product-mission fit and integration pathways. Phase II focuses on maturing the framework, tailoring it to pLEO architectures, and demonstrating a prototype. Phase III will transition the capability into operational use for PWSA and other pLEO constellations, focusing on scalability, commercialization, and sustainment to enhance mission assurance and reduce costs.
    1765929753555.pdf
    The Space Development Agency (SDA) seeks innovative solutions for an adaptive, knowledge-guided test-planning capability to support the Proliferated Warfighter Space Architecture (PWSA), a continuously evolving Low Earth Orbit (LEO) constellation. Traditional test strategies are insufficient for SDA's rapid, tranche-based deployments. The objective is to develop a modern test framework that continuously updates system performance using real-time data, quantifies knowledge gain versus resource cost, and dynamically re-plans test sequences to prioritize high-utility activities. Solutions should incorporate probabilistic reasoning (e.g., Bayesian inference), integrate synthetic and live test data, and use multi-objective utility models aligned with mission priorities. This Direct-to-Phase II effort requires applicants to demonstrate a
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