HOW TO ACCESS CONTRACTS
The Space and Missile Systems Center (SMC) Remote Sensing Systems Directorate (SMC/RS) intends to solicit proposals through the use of a Broad Agency Announcement (BAA) for research on advanced technologies to enhance processing of space-based remote sensor mission data and dissemination of the resulting information products.
Visit the link below to read about the latest opportunity (Solicitation 16-086).
Awarded: BAA Call #3
Congratulations to the following companies and organizations on the award of the following BAA contracts under Call 3.
Multiple Integration Normalization Interfaces (MINI) will provide discrete capabilities delivering a defined, repeatable and a reliable infrastructure in which vendors will be able to access the UNCLASSIFIED resources they need. MINI capabilities fall into two functional groups: Capabilities 1 and 2 provide a means to deliver UNCLASSIFIED data (MODIS, VIIRS, GOES, Mark IV-B, and AWIPS) and visualization services (NGA's Global Enhanced GEOINT Delivery, GEOINT Visualization Services, and OpenStreetMaps) to the TAP Lab SECRET enclave. Capability 3 provides a sanitized UNCLASSIFIED data product in support of the United States Forest Service (USFS).
Persistent, Periodic Preprocessing Services (3P Services) will enhance the TAP Lab and OPIR Battlespace Awareness Center (OBAC) by creating a complementary open framework, accelerating development teams with preprocessing tasks to prepare sensor data for non-real-time and periodic applications. The 3P Services framework will feed all periodic applications, as the Highly Efficient Mission Integration (HEMI) feeds all real-time applications. The 3P services, utilities, and libraries will be well documented, and an online catalog will enable developers and users to discover, search, and contribute. 3P Services will align with the Open Framework Architecture (OFA) approach, using open standards and open source software.
AI-based Assimilation of OPIR Data will fuse Overhead Persistent Infrared (OPIR) data with conventional Meteorological Satellite (METSAT) data to derive rapidly updated atmospheric motion vectors (AMVs) for direct assimilation into Numerical Weather Prediction (NWP) models to enhance mission-critical Battlespace Awareness (BA), particularly in data deprived regions of the world. Specifically, this project will apply Artificial Intelligence (AI) and machine learning techniques, coupled with extensive modeling and data assimilation, to enable the fusion of OPIR data with conventional geostationary METSAT data. The rapid refresh associated with the OPIR-METSAT Fusion (OMF) process will enable the derivation of “enhanced” AMVs for direct assimilation into Numerical Weather Prediction (NWP) models. This project will develop a (MATLAB based) prototype OMF-AMV Generator that will leverage OPIR and traditional METSAT imagery to derive fused AMV products formatted for direct assimilation into NWP models.
Weather Radar for the TAP Lab will enhance access to available data sets through the addition of weather radar ingest and data adaptation capabilities for the Sensor Open Framework Architecture (SOFA). The solution would allow the TAP Lab (and any environment leveraging SOFA) to ingest real-time and near-real-time weather radar volumes over direct or service-based connections respectively. The data would also be adapted for output via the existing SOFA Application Programming Interface (API) to allow for ingest by processing applications.
OBAC Mission Network Integration (OMNI) will develop and employ a User Experience providing the operator with customizable workflow centered automation and visualization and a true ‘set it and forget it’ technology capability that provides a comprehensive warfighter tool to receive alerts, analyze, and be informed across any number of diverse data sets. Utilizing a distinctive technology set currently in operations at the National Space Defense Center (NSDC), and other operating locations. The framework provides a unique set of automation tools with continuously running jobs and customizable rulesets, both alerting the user and monitoring complex situations—completely user configurable with seamless rapid setup.
The objective of the Web-Enabled COP for TAP and OBAC is to deploy a modification of the commercial Outly platform as a demonstrational Common Operational Picture (COP) solution. The Outly platform enables a state-of-the-art, web-enabled user interface for operators and developers in the UTAP, TAP and optionally the OBAC. A modified Outly user interface would provide operators and developers with selection panels and data displays to allow rapid discovery and inspection of TAP/OBAC data. Specifically, the UI and backend data ingest will be modified and configured for the TAP Lab and OBAC use case to provide operators and developers with an intuitive and performant display for discovering, viewing, analyzing and annotating data sets.
Awarded: BAA CALL #2
Congratulations to the following companies and organizations on the award of the following BAA contracts under Call 2.
Building on the Weather Applications of Advanced Military Infrared Systems (WAAMIR) Project, OWTCA will continue and extend that work to provide a validated and integrated capability in the TAP Lab for weather and other environmental applications. Additionally, this applicaiton will develop an Improved Target Typing and Characterization Toolkit (ITTC) that will significantly improve detection and tracking of time-critical targets with Overhead Persistent Infrared (OPIR) assets.
The Fusion of OPIR Non-Traditional Data for Improved GEO SSA (FONTDIGS) development is intended to (i) assess the extent to which data collected by star-trackers onboard overhead persistent infrared (OPIR) sensor platforms in GEO and HEO, as well as the OPIR track data itself, can be utilized for uncorrelated track (UCT) processing in support of improved GEO SSA (i.e., at altitudes outside the range of most radars, with a focus on GEO and near-GEO), and (ii) combine this data with high-quality observations collected by Numerica’s global telescope network in order to quantify the potential benefit of fusing such multi-sensor, multi-target data.
Machine Learning Tecnologies for Event Detection will deliver a software package that applies machine learning technologies for detection, characterization, and continuous monitoring of events and dim targets in SBIRS data.
Global Cropland Fire Sensing and Characterization Using SBIRS Data is to evaluate SBIRS data for sensing cropland burning as well as the estimation of the associated pyrogenic emissions, adapt existing fire detection and characterization algorithms for use with SBIRS data within the context of cropland burning, produce combusted cropland-residue biomass and cropland-residue black carbon/trace gas emissions data sets, and compare these data sets to estimates derived from conventional sensors as well as expert, ground-based bottom up inventories.
Cross Calibration of TAP Lab Sensors will contribute to the User Experience in the TAP Lab by creating more consistent datasets. Ultimately, the goal of this effort is to provide calibration coefficients for the OPIR sensors that bring the OPIR radiometric uncertainties more in line with atmospheric remote sensing applications and ensure data consistency between the current TAP Lab datasets.
Enhanced Resolution for Scenes and Closely Spaced Targets will develop, evaluate, and optimize enhanced resolution (ER) techniques for application to the real-time continuous Space-Based Infrared System (SBIRS) data streams from the Highly Efficient Mission Integrator (HEMI) framework.
Effort will develop a prototype Battlespace Enhanced Anomaly Discrimination System (BEADS) software. The software system will process OPIR live data to identify and report anomalous events within an area of interest.
The objective of the Battlespace Awareness Target Geolocation and Identification using Reinforced Learning (BATGIRL) is to develop, deliver, and test a real time capable classification module with APIs for ingest of mono and multi-sensor object messages along with generalized libraries for correlation, geolocation and initial heading estimation. BATGIRL also provides generalized libraries for probabilistic fusion along with the essential classification functions to positively identify the highest priority threats to joint air force operations with a low false typing rate when the highest temporal fidelity data streams are available.
The Dynamic Functions for Exploitation of Advanced Threats (DFEAT) will leverage persistent sensing capabilities to detect new classes and variants of offensive missiles such as Anti Access/Area Denial (A2/AD) systems to the Tools, Applications, and Processing (TAP) Lab.
Awarded: BAA CALL #1
Congratulations to the following companies and organizations on the award of the following BAA contracts under Call 1.
Advanced High-G Dynamics Tracking Solution is to develop and demonstrate a new SBIRS tracking system to address critical needs for tracking new high-g dynamics missile threats.
Network-Independent Open-Standard Messaging Service (NOMS) Enhancements (NOMS-E) is aimed at evolving the current message dissemination capability to a more flexible solution to service Unclassified message receipt with providing a secure (automated) method for fusing Unclassified data into a Secret enclave.
Ice Change and Arctic Transportation Application (ICARTA) for Civil, Environmental and Military Use will leverage OPIR capabilities to develop the Ice Characterization in Artic Regions for Transportation Application (ICARTA). ICARTA will consist of maps of sea ice around Alaska to support the shipping and land transportation industries.
IntersectTM Exploit combines OPIR data with an existing National Weather service visualization tool, the Universal Framework (uFrameTM). The application ingests Space Based Infrared System (SBIRS) data and displays it concurrently with Visible Infrared Imaging Radiometer Suite (VIIRS) data.
Collaborative Analyst-Machine Perception for Robust Data Fusion (CAMP) is to develop new fusion algorithms and interfaces that promote online collaborative human-machine perception for robust data analysis and fusion. The key idea is to allow analysts to communicate directly with automated machine learning algorithms via natural language chat, direct manipulation, and hand-drawn locative sketches. Probabilistic machine learning, data fusion, and human input processing algorithms will be combined into a unified software suite that enables bilateral information exchange between automation and analysts.
Flexible Feature Extraction, Data Fusion, and Object Classification Framework (FFEOT) is to enable automated extraction of features from SBIRS imagery and implement a flexible data fusion and typing framework to address many civil and defense applications.
Atmospheric Correction Toolkit for OPIR Applications (ACT) is to develop an integrated set of software tools that perform atmospheric correction operations and can be used as plug-in components with algorithms and other applications that utilize Overhead Persistent Infrared (OPIR) data.
Power Walker is an integration solution that develops an intelligent combination of multiple applications from various industry on the SOFA framework with the objective of meeting the PowerWalker JEON.
The objective of the Fast and Flexible Multi-environment App Deployment and Scaling (F2MADS) application is the development of a container-based platform for the TAP Lab and OBAC, including supporting tools to deploy, manage, and orchestrate containerized applications and services to provide flexible configuration and command selection.
Automated Dim Transient Event Detection focuses on optimization, implementation, and integration of an end-to-end clutter suppression and dim event detection algorithm for the Space Based Infrared System (SBIRS). In particular, this effort will focus on the development of an advanced processing software package in a standalone application capable of being run on a single desktop computer/workstation.