You are here
Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
-
Faster Optical Modem for Underwater Data Acquisition
SBC: SA PHOTONICS, LLC Topic: NGA182001SA Photonics’ Optical Navigation and Ranging (ONAR) system is an interrogative system that operate underwater in wavelength range of blue/green (450-540 nm) and enables navigational correction to IMU based dead reckoning navigation. The location based beacons are battery operated and have operational life span of over one year. The system is designed to operate in on demand burst mode so that no ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Faster Optical Modem for Underwater Data Acquisition
SBC: SONALYSTS INC Topic: NGA182001To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
A Multi-Branch Network for Automated VNIIRS Assessment of Motion Imagery
SBC: TOYON RESEARCH CORPORATION Topic: NGA191003Due to the lack of consistency in existing automated methods for assigning VNIIRS levels to motion imagery, and the overwhelming human resources required to manually assign levels, a new method of automated/semi-automated VNIIRS assessment is needed. In recent years, advancements in deep learning have provided solutions to previously intractable computer vision problems. In many cases, automated d ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Collaborative Recommender System for Spatio-Temporal Intelligence Documents
SBC: NUMERICA CORPORATION Topic: NGA191005US military and intelligence agencies have invested significant resources in data collection and effective search and analytics tools. However, due to increasing amounts of data, finding relevant information has become more difficult. Thus, there is an important need for recommender system technology that pushes relevant un-queried data to analysts through automation and machine learning technique ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
ALARM: Adversarially-learned Labels using Activity and Reward Models
SBC: APTIMA INC Topic: NGA191006Technological advances in navigation and positioning, along with expanding wireless infrastructure and remote sensing technologies, have resulted in an explosive growth of available trajectory data from a variety of moving objects, such as people, cars, ships, or animals. Traditional trajectory mining algorithms do not explain how and why the motion was generated, limiting their utility in GEOINT ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Gamified Analysis Tasks for Heightened Engagement across Repetitions (GATHER)
SBC: CHARLES RIVER ANALYTICS, INC. Topic: NGA191007At the National Geospatial-Intelligence Agency (NGA), the ability to serve and analyze data is crucial to the success of efforts ranging from disaster relief to strategic military support. NGA recently created the Office of Automation, Augmentation, and Artificial Intelligence (AAA) which has a goal “to automate routine tasks to give crucial time back to employees.” These automated systems mus ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Innovative methods for detecting and characterizing electrical grid topologies and induced electrical power transient events from lights
SBC: Systems & Technology Research LLC Topic: NGA191010STR is proposing to implement monitoring of power grid state via high-speed, wide-field optical photometry. We will design, test, and implement algorithms on commercially available hardware with the intent of deriving grid topology in addition to detecting, characterizing, and geolocating anomalous events. We will also evaluate fusing the photometry-derived data with other data sources available t ...
SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Advanced Image Segmentation for Radar Imagery
SBC: ELECTROMAGNETIC SYSTEMS, INC. Topic: NGA172004Implement methods to improve our Phase I architecture for complex SAR imagery collected from different systems and with different collection parameters. Implement techniques to boost performance across all ground features of interest. Reduce the amount of human intervention needed for training our SAR image segmentation architecture. SAR segmentation can be applied to a number of areas: Intellig ...
SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Low-Shot Detection in Remote Sensing Imagery
SBC: TOYON RESEARCH CORPORATION Topic: NGA172002Toyon Research Corporation proposes to develop algorithms that improve the precision and recall of neural networks for low-shot object classification and detection. Our approach is based upon developing a descriptive multi-domain feature representation of the low-shot target as well as the surrounding context. A multi-branch neural network merges the various domains of information to perform accur ...
SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency -
Generalized Change Detection to Cue Regions of Interest
SBC: TOYON RESEARCH CORPORATION Topic: NGA181006Toyon proposes to research and develop algorithms for generalized salient change detection, and to incorporate these algorithms into software tools implemented on the cloud. Our approach leverages the two most promising methods from Phase I, both based on supervised learning. The first method is the entropy-based feature vector and corresponding neural network, which we will apply at a coarse sear ...
SBIR Phase II 2019 Department of DefenseNational Geospatial-Intelligence Agency