ONHS Report: FA875024S7005

ADVANCED RESEARCH ANNOUNCEMENT (ARA) TITLE: CHARACTERIZATION AND ASSESSMENT FOR SPACE DOMAIN AWARENESS (SDA)

Solicitation ID: FA875024S7005

Agency: AFRL/Information Directorate

Type: Presolicitation

Deadline: 2029-07-12T17:00:00 ET

Eligibility: Maybe (Dual Approval Required)

Funding: Total funding of approximately $99M. Individual awards will normally range from $1M to $10M, with the potential for awards up to the total ceiling amount.

Doc Type: BAA

Clearance: Top Secret

Program Manager: Carolyn Sheaff

Last Updated: 2025-11-24 13:09

Analyzed File: ARA 24-05 SAM Synopsis Open ARA - SDA v7.docx

Eligibility Reasoning

FFRDCs: FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector; and FFRDCs must provide a letter on official letterhead from their sponsoring organization citing the specific authority establishing their eligibility to propose to Government solicitations and compete with industry, and their compliance with the associated FFRDC sponsor agreement’s terms and conditions. This information is required for FFRDCs proposing to be prime contractors or sub-awardees.

Note: This is an AI-generated summary...

Summary

This Advanced Research Announcement (ARA FA8750-24-S-7005) from the Air Force Research Laboratory sought research to design, develop, and test technologies supporting Space Domain Awareness (SDA) and Space Superiority. Key technical areas included intelligent tasking, multi-source data fusion (from radar, optical, SIGINT, OSINT), high-performance computational analysis, automated pattern/anomaly detection, satellite modeling, and astrodynamics algorithm development to create an integrated, predictive SDA capability. The total estimated funding was approximately $99M, with multiple awards anticipated as contracts or Other Transactions. IMPORTANT: According to an amendment, this ARA has been cancelled and is no longer accepting submissions.

Overall Technical Areas

Space Domain Awareness (SDA)Intelligent Sensor TaskingHigh-Performance ComputingAutomated Pattern LearningSpace Event Anomaly DetectionMulti-Source Data FusionSpace Object CharacterizationSatellite Modeling & SimulationSatellite Vulnerability AssessmentAstrodynamics Algorithm DevelopmentResident Space Object (RSO) TrackingOptical Detection TechniquesImage Processing AlgorithmsPredictive Data Analysis

Probable LBNL Areas

BSACSAEESAETALDPSA

Focus Areas

Example Priorities:

Automated pattern learning and reasoning, anomaly detection and characterization and assessment of space events.

Specific Technical Skills:

Machine LearningPattern RecognitionAnomaly DetectionAI ReasoningSpace Event CharacterizationSpace Domain AwarenessData ScienceTime-Series Analysis

Potential PIs for this Area:

Name	Score	Organization
Alexander Sim	0.72	CSA \| SciData \| Data Science Research
Shawn Tornga	0.72	LD \| LD \| ONHS
Zhe Bai	0.71	CSA \| AMCR \| Computer Science
Gazi Mahmud	0.71	BSA \| Environmental Genomics & Systems Biology \| Molecular Ecosystems Bio
Marco Salathe	0.70	PSA \| NSD \| ANP
Ana Comesana	0.70	ETA \| Building Technology & Urban Systems \| Bldg & Industrial App Dpt
Wahid Bhimji	0.70	CSA \| NERSC \| Sci Eng & Workflows Department
Ana Kupresanin	0.70	CSA \| Computing
Nicola Falco	0.69	EESA \| CESD \| Integrated Ecosystem Sciences
Marco Pritoni	0.69	ETA \| Building Technology & Urban Systems \| Bldg Technologies Dept

Example Priorities:

Multi-source data (radar, optical and other) exploitation, analysis and fusion for timely, accurate and complete characterization of space objects.
Mathematical approaches for fusing, assessing and characterizing data from new sensor and information sources.
Information sources include Signals Intelligence (SIGINT), Image Intelligence (IMINT), Moving Intelligence (MOVINT), Human Intelligence (HUMINT), Open Source Intelligence (OSINT), Twitter, Facebook, weather (space and terrestrial), non-resolvable imagery and the orbital catalog.

Specific Technical Skills:

Data FusionSensor FusionMulti-INT AnalysisSIGINTIMINTOSINTRadar Data ProcessingOptical Data AnalysisStatistical ModelingNon-resolvable Imagery

Potential PIs for this Area:

Name	Score	Organization
Shawn Tornga	0.69	LD \| LD \| ONHS
Alexander Sim	0.69	CSA \| SciData \| Data Science Research
Gazi Mahmud	0.69	BSA \| Environmental Genomics & Systems Biology \| Molecular Ecosystems Bio
Boris Faybishenko	0.68	EESA \| EG \| Hydrogeology Dept
Nicola Falco	0.68	EESA \| CESD \| Integrated Ecosystem Sciences
Zhe Bai	0.68	CSA \| AMCR \| Computer Science
Ana Kupresanin	0.68	CSA \| Computing
Marco Salathe	0.68	PSA \| NSD \| ANP
Marcos Lopez de Prado	0.68	CSA \| SciData \| Data Science Research
Edward Bethel	0.67	CSA \| SciData \| Data Science Research

Example Priorities:

High fidelity tools for satellite modeling, classification and vulnerability assessment.
Algorithms, techniques and approaches for satellite detection, tracking, identification and recognition; new approaches for optical detection, image processing and computing; analysis required for modeling and simulation.
Innovative techniques and approaches for Resident Space Object (RSO) detection and tracking, new approaches to optical, image processing and computing

Specific Technical Skills:

Satellite ModelingObject DetectionObject TrackingComputer VisionImage ProcessingVulnerability AssessmentModeling and SimulationResident Space Object (RSO) TrackingHigh-Performance Computing

Potential PIs for this Area:

Name	Score	Organization
Shawn Tornga	0.71	LD \| LD \| ONHS
Alexander Sim	0.70	CSA \| SciData \| Data Science Research
Emil Rofors	0.69	PSA \| NSD \| ANP
Edward Bethel	0.68	CSA \| SciData \| Data Science Research
Samuel Williams	0.68	CSA \| AMCR \| Computer Science
Jean Luca Bez	0.68	CSA \| SciData \| Data Science Research
Nicola Falco	0.68	EESA \| CESD \| Integrated Ecosystem Sciences
Zhe Bai	0.68	CSA \| AMCR \| Computer Science
Marco Salathe	0.68	PSA \| NSD \| ANP
Oluwamayowa Amusat	0.68	CSA \| SciData \| Data Science Applications

Example Priorities:

Astrodynamics algorithm development

Specific Technical Skills:

AstrodynamicsOrbital MechanicsAlgorithm DevelopmentNumerical MethodsCelestial MechanicsPredictive ModelingSpacecraft DynamicsTrajectory OptimizationKalman Filtering

Potential PIs for this Area:

Name	Score	Organization
Chad Mitchell	0.68	PSA \| ATAP \| Advanced Modeling Prog
Louis-Benoit Desroches	0.68	ETA \| Energy Analysis & Environmental Impacts \| Energy Efficiency Studies
Zhe Bai	0.68	CSA \| AMCR \| Computer Science
Sofia Hamilton	0.68	ETA \| Energy Analysis & Environmental Impacts \| Energy Markets & Policy
Andre Santos	0.68	EESA \| CESD \| Integrated Ecosystem Sciences
Emil Rofors	0.68	PSA \| NSD \| ANP
Reijo Keskitalo	0.67	CSA \| SciData \| Data & Computational Science
Ann Almgren	0.67	CSA \| AMCR \| Applied Mathematics
Hannah Klion	0.67	CSA \| AMCR \| Applied Mathematics
Andrew Myers	0.67	CSA \| AMCR \| Applied Mathematics

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

Name	Score	Organization
Lisa Claus	0.76	CSA \| NERSC \| Sci Eng & Workflows Department · High-Performance Computing
Igor Jovanovic	0.75	PSA \| NSD \| ANP · Optical Detection Techniques
Houjun Tang	0.74	CSA \| SciData \| Data Science Applications · Image Processing Algorithms
Wei Zhang	0.73	CSA \| SciData \| Data Science Research · Intelligent Sensor Tasking
Michael Mahoney	0.73	CSA \| SciData \| Data Science Research · Predictive Data Analysis
Mark Bandstra	0.73	PSA \| NSD \| ANP · Space Event Anomaly Detection
Edward Schlafly	0.73	PSA \| PHY \| Dark Energy · Space Object Characterization
Anna Giannakou	0.73	CSA \| SciData \| Data Science Applications · Automated Pattern Learning
Satyarth Praveen	0.73	CSA \| SciData \| Data Science Applications · Multi-Source Data Fusion
Shawn Tornga	0.73	LD \| LD \| ONHS · Space Domain Awareness (SDA)

Fundamental Research Exemption (FRE)

As of the date of publication of this ARA, the Government does not anticipate work proposed under this ARA to be considered fundamental research. Proposers should indicate in their proposal whether they believe the scope of the research included in their proposal is fundamental or not. While proposers should clearly explain the intended results of their research, the Government shall have sole discretion to select award instrument type and to negotiate all instrument terms and conditions with selectees. Appropriate clauses will be included in resultant awards for non-fundamental research to prescribe publication requirements and other restrictions, as appropriate.