ONHS Report: HM047627XXXX

NGA - Boosting Innovative GEOINT - Science & Technology Broad Agency Announcement (BIG-ST BAA): Topic # 07 – Lidar Analysis for Surface & Environmental Reconnaissance (LASER)

Solicitation ID: HM047627XXXX

Agency: NGA

Type: Solicitation

Deadline: 2026-12-11T23:59:00 ET

Eligibility: Maybe (Dual Approval Required)

Funding: A subcontracting plan is required for contracts expected to exceed $750,000.00.

Doc Type: BAA

Clearance: No

Program Manager: BIGSTBAA@nga.mil

Last Updated: 2026-10-02 16:04

Analyzed File: BIGST_BAA_HM047623BAA00001_GeneralSolicitation_REV4_20260730.pdf

Eligibility Reasoning

FFRDCs are subject to applicable direct competition limitations and cannot propose to this BAA in any capacity unless they meet the following conditions: (1) FFRDCs must clearly demonstrate that the proposed work is not otherwise available from the private sector; (2) FFRDCs must provide a letter, on official letterhead from their sponsoring organization, that (a) cites the specific authority establishing their eligibility to propose to Government solicitations and compete with industry, and (b) certifies the FFRDC’s compliance with the associated FFRDC sponsor agreement’s terms and conditions...

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

Summary

The National Geospatial-Intelligence Agency (NGA) is soliciting innovative research and development proposals under the Boosting Innovative GEOINT - Science & Technology (BIG-ST) Broad Agency Announcement (BAA), HM0476-23-BAA-0001. The BAA aims to address challenging Geospatial-Intelligence (GEOINT) problems to support U.S. national security. This is a general solicitation under which specific "Topic Calls," such as the active "Topic #07 – Lidar Analysis for Surface & Environmental Reconnaissance (LASER)," are released. Proposed research must fall within Technology Readiness Levels (TRL) 1-7 and align with one of three technical domains: (1) Foundational GEOINT, focusing on high-resolution Earth representations; (2) Advanced Phenomenologies, involving novel data sensing and processing; and (3) Analytic Technologies, leveraging AI/ML, computer vision, and advanced analytics. The process requires a mandatory abstract submission for a specific Topic Call before a full proposal can be submitted. The government may issue various award types, including procurement contracts, grants, cooperative agreements, or Other Transactions (OTs).

Overall Technical Areas

Geodetic & Geophysical ModelingAssured Positioning & NavigationAutomated Feature ExtractionHuman & Environmental ModelingBathymetric & Topographic ModelingAdvanced Sensor Data ProcessingTarget Detection & TrackingNovel Source ExploitationSpace Situational AwarenessMulti-Domain Data AggregationArtificial Intelligence & Machine LearningComputer Vision & Image UnderstandingAutomated Target Recognition (ATR)Predictive Analytics & ForecastingKnowledge & Ontology Modeling

Probable LBNL Areas

BSACSAEESAESAETAPSA

Focus Areas

Example Priorities:

The Foundational GEOINT portion of the Research portfolio focuses on the creation of always accurate, high-resolution, continually updated representations of the earth’s properties, available on demand.
Innovations advancing the GEOINT physical sciences in the areas of: terrestrial/celestial reference frames; earth gravitational models; world magnetic models.
Assured positioning, navigation and timing, and resilience.
Feature extraction, attribution, classification and modeling.
Human geography and environmental models.
Bathymetric/topological models; and maritime environmental mapping.

Specific Technical Skills:

GeodesyGeophysicsGravimetryMagnetometryPositioning, Navigation, and Timing (PNT)GeopositioningRemote SensingGeospatial Data ModelingBathymetryGeographic Information Systems (GIS)

Potential PIs for this Area:

Name	Score	Organization
David Alumbaugh	0.77	EESA \| EG \| Geophysics Dept · Geophysics
Florian Soom	0.77	EESA \| EG \| Geophysics Dept · Geophysics
Craig Ulrich	0.77	EESA \| EG \| Geophysics Dept · Bathymetry
Yuankun Xu	0.76	EESA \| EG \| Geophysics Dept · Remote Sensing
Sylvain Fiolleau	0.76	EESA \| EG \| Geophysics Dept · Geopositioning
Roland Burgmann	0.75	EESA \| EG \| Geophysics Dept · Geodesy
Wei Zhang	0.75	CSA \| SciData \| Data Science Research · Geospatial Data Modeling
Cynthia Gerlein-Safdi	0.75	EESA \| CESD \| Integrated Ecosystem Sciences · Remote Sensing
Marta Gonzalez	0.73	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Geographic Information Systems (GIS)
Sophie Morley	0.72	ESA \| ALS \| ALS Photon Science Operations · Magnetometry

Example Priorities:

The Advanced Phenomenologies portion of the Research portfolio employs novel methods and efficient strategies to drive development and delivery of improved spatially, spectrally, radiometrically, polarimetrically, and temporally resolved data from a growing number of traditional and non-traditional sources.
Detection, tracking, and identification of the most challenging targets in complex environments.
Sensing and real-time processing of both static and dynamic targets.
Novel source exploitation and optimization.
Collection technologies to optimize use of phenomenology sources.
Space situational awareness.
Information assurance, data integrity and quality validation.
Multi-domain data aggregation.

Specific Technical Skills:

Sensor PhysicsSignal ProcessingRemote Sensing SystemsRadiometrySpectroscopyPolarimetryTarget Detection & TrackingAlgorithm DevelopmentData FusionSpace Situational Awareness (SSA)

Potential PIs for this Area:

Name	Score	Organization
Daniel Feldman	0.76	EESA \| CESD \| Earth System Sciences · Remote Sensing Systems
Yuankun Xu	0.76	EESA \| EG \| Geophysics Dept · Remote Sensing Systems
Oliver Gessner	0.75	ESA \| CSD · Spectroscopy
Yuan Mei	0.75	PSA \| PHY \| Atlas · Sensor Physics
Nicola Falco	0.74	EESA \| CESD \| Integrated Ecosystem Sciences · Signal Processing
Oscar Antepara	0.74	CSA \| AMCR \| Computer Science · Algorithm Development
Akito Kusaka	0.74	PSA \| Physical Sciences \| Physics · Polarimetry
Emil Rofors	0.73	PSA \| NSD \| ANP · Target Detection & Tracking
Gregory Lemieux	0.73	EESA \| CESD \| Earth System Sciences · Space Situational Awareness (SSA)
Wei Zhang	0.73	CSA \| SciData \| Data Science Research · Data Fusion

Example Priorities:

The Analytic Technologies portion of the Research portfolio enhances the definition and utility of GEOINT by leveraging new sources of data and developing novel analytic techniques to deliver a geospatial dimension to multi-INT analytics...
Geospatial signatures detection, analysis, and tracking.
Image/video understanding and computer vision.
Automated target recognition.
Temporal and activity modeling and contextualization.
Event forecasting and prediction.
Artificial intelligence, to include novel learning techniques.
Human-machine interaction.
Tools to guide algorithm and automation governance.
Immersive GEOINT visualization tools.

Specific Technical Skills:

Machine LearningArtificial IntelligenceComputer VisionAutomated Target Recognition (ATR)Spatiotemporal AnalysisPredictive AnalyticsKnowledge RepresentationNatural Language Processing (NLP)Human-Computer Interaction (HCI)Data Visualization

Potential PIs for this Area:

Name	Score	Organization
Josh North	0.75	EESA \| CESD \| Earth System Sciences · Spatiotemporal Analysis
Talita Perciano Costa Leite	0.74	CSA \| SciData \| Data Science Research · Machine Learning
Matthew Henderson	0.74	CSA \| SciData \| Data Science Applications · Natural Language Processing (NLP)
Satyarth Praveen	0.74	CSA \| SciData \| Data Science Applications · Computer Vision
Michael Mahoney	0.73	CSA \| SciData \| Data Science Research · Predictive Analytics
Anna Giannakou	0.73	CSA \| SciData \| Data Science Applications · Artificial Intelligence
Tanny Andrea Chavez Esparza	0.73	ESA \| ALS \| PS Computing staff · Automated Target Recognition (ATR)
Annette Greiner	0.73	CSA \| NERSC \| Sci Eng & Workflows Department · Data Visualization
Drew Paine	0.72	CSA \| SciData \| Data Science Applications · Human-Computer Interaction (HCI)
Chris Mungall	0.71	BSA \| Env. Genomics & Sys. Biology \| BioSystems Data Science · Knowledge Representation

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
David Alumbaugh	0.76	EESA \| EG \| Geophysics Dept · Geodetic & Geophysical Modeling
C. Anna Spurlock	0.75	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Human & Environmental Modeling
Marta Gonzalez	0.74	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Predictive Analytics & Forecasting
Houjun Tang	0.74	CSA \| SciData \| Data Science Applications · Advanced Sensor Data Processing
Victor Negut	0.74	PSA \| NSD \| ANP · Target Detection & Tracking
Talita Perciano Costa Leite	0.73	CSA \| SciData \| Data Science Research · Artificial Intelligence & Machine Learning
Satyarth Praveen	0.73	CSA \| SciData \| Data Science Applications · Automated Feature Extraction
Gazi Mahmud	0.73	BSA \| Env. Genomics & Sys. Biology \| Molecular Ecosystems Bio · Knowledge & Ontology Modeling
Mark Bandstra	0.72	PSA \| NSD \| ANP · Novel Source Exploitation
Alexandre Bayen	0.72	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Assured Positioning & Navigation

Fundamental Research Exemption (FRE)

Fundamental Research – Basic and applied research in science and engineering, the results of which ordinarily are published and shared broadly within the scientific community, as distinguished from proprietary research and from industrial development, design, production, and product utilization, the results of which ordinarily are restricted for proprietary or national security reasons. Refer to National Security Decision Directive (NSDD) 189 (dated 21 SEP 1985) and complimentary DOD Policy memorandums (ATL Memorandum, DoD Policy on Fundamental Research dated 26 JUN 2008 and 24 MAY 2010).