You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

  1. Vehicle Reidentification-Aided Network Topology Inference (VRANTI)

    SBC: Systems & Technology Research LLC            Topic: NGA201005

    Systems & Technology Research (STR) proposes to develop Vehicle Reidentification-Aided Network Topology Inference (VRANTI), a novel system for estimating proximity network graphs of traffic cameras to facilitate intelligence applications such as tracking and monitoring of traffic systems. Network inference will be performed using statistical analyses of features extracted from camera video feeds, ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  2. Hybrid Machine Learning Approaches for Radiation Signature Identification

    SBC: Radiation Monitoring Devices, Inc.            Topic: NGA192002

    To improve the identification and detection of radio-logical materials, we propose a hybrid supervised learning and unsupervised machine learning approach to reduce the false positive rate, increase the accuracy and throughput, and augment the capabilities of the human operators. At the end of the Phase I, we will have a machine learning algorithm that is trained to recognize a variety of nuclear ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  3. Radioactive Anomaly Detection and Identification Algorithm Suite (RADIAS) for Enhanced Radiological Search

    SBC: Physical Sciences Inc.            Topic: NGA192002

    Physical Sciences Inc. (PSI) proposes to develop an advanced machine learning (ML) algorithm to detect threat-based anomalies in gamma-ray spectra in real-time. If a network of distributed R/N sensors is employed, the algorithms will also be capable of tracking such anomalies through the network. The Radiation Anomaly Detector (RAD) will be packaged with PSI’s award winning Poisson Clutter Spli ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  4. High Efficiency Semiconductors for Nuclear Detection

    SBC: Radiation Monitoring Devices, Inc.            Topic: NGA192003

    There is a need for low cost, high performance gamma-ray detectors for national and homeland security applications for detection, identification and localization of special nuclear materials. Common detectors used in this application include scintillators coupled to photomultiplier tubes or silicon photodiodes, and semiconductor detectors like cadmium zinc telluride. Semiconductor detector offer ...

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  5. Perovskite-based Multi-modal Detector and Imaging System

    SBC: CAPESYM, INC            Topic: NGA192003

    Perovskites are rapidly emerging as attractive radiation detectors. The goal of this program is to develop a multi-modal detection sensor based on perovskite materials. The developed detector will be integrated with a high resolution active pixel array and the pixel signals will be processed by high speed electronics to create scene images of different radiation types.

    SBIR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
  6. Remote Sensor Data Protection and Anti-Spoofing

    SBC: BlueRISC, Inc.            Topic: DHS201002

    Phase I project will be the investigation and specification of the necessary algorithms and platform for detection and mitigation of spoofing attacksand compromised sensing in sensor networks. The solution addresses the three main areas of sensing security: (a) detection and mitigation with corresponding customization; (b) support for collaborative, distributed detection across Ndes; and (c) hardw ...

    SBIR Phase I 2020 Department of Homeland Security
  7. One dimensional convolutional neural networks for improved training time and standardization in spectral classification

    SBC: Physical Sciences Inc.            Topic: DHS201009

    Physical Sciences Inc. (PSI) proposes to develop a deep learning based spectral target detection algorithm for identification and classification of opioids and explosives that will be executed on a portable hardware solution. The proposed algorithm is designed to be spectrometer agNstic and allows for rapid training on previously untrained spectrometer platforms. The proposed hardware solution is ...

    SBIR Phase I 2020 Department of Homeland Security
  8. Innovative methods for detecting and characterizing electrical grid topologies and induced electrical power transient events from lights

    SBC: Systems & Technology Research LLC            Topic: NGA191010

    STR 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
  9. Gamified Analysis Tasks for Heightened Engagement across Repetitions (GATHER)

    SBC: Charles River Analytics, Inc.            Topic: NGA191007

    At 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
  10. ALARM: Adversarially-learned Labels using Activity and Reward Models

    SBC: Aptima, Inc.            Topic: NGA191006

    Technological 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
US Flag An Official Website of the United States Government