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 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.

  1. Power and Rechargeable Battery Interface Smart Module

    SBC: INTELLISENSE SYSTEMS INC            Topic: HSB0191003

    To address the DHS need for a module that can power/charge and provide effective power management of all on-body electronics including sensors, communications systems, and peripheral devices for all first responder mission areas, Intellisense Systems, Inc. (ISI) proposes to develop a new Power and Rechargeable Battery Interface Smart Module (PRISM). This proposed technology is based on a novel mod ...

    SBIR Phase I 2019 Department of Homeland Security
  2. Cybersecurity Peer-to-Peer Knowledge/Lessons Learned Tool

    SBC: INFERLINK CORP            Topic: HSB0191006

    The increasing number of breaches and hacks against organizations demands new and more effective ways to provide defense. Currently, most defense activities, such as monitoring, analysis, forensics, and remediation are done within house. This is unfortunate because the external knowledge and experience of others outside the organization cannot easily be leveraged. Our proposal focuses on the desig ...

    SBIR Phase I 2019 Department of Homeland Security
  3. Critical Program Information (CPI) Identification and Assessment Tool

    SBC: Management Analysis Network, LLC, The            Topic: SCO183002

    Protecting the effectiveness of US advanced weapon systems and the technology they rely on is a national priority. Unfortunately, individuals tasked with this mission are met with disjointed guidance, no training, and competing processes to consider. It is no wonder adversaries continue to exploit these weaknesses in the Department of Defense (DOD); stealing our Critical Program Information (CPI) ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  4. Multi-Sensor Fire Control System for Tracking Highly Maneuverable Targets

    SBC: VENATOR SOLUTIONS, LLC            Topic: SCO182005

    Recent advances in aeronautical design and development has contributed to a significant increase in the vulnerability of the warfighter’s land and sea-based assets from threat-targets exhibiting unpredictable, high-dynamic motion, evasive control, and countermeasure usage. The primary defensive strategy against these targets is a fire control radar system. These systems typically use a sing ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  5. Scalable Low-Cost AESA Transmitter with Phase-Only Nulling

    SBC: TECHNOVATIVE APPLICATIONS            Topic: SCO182002

    Active electronically scanned antennas (AESA) for radar have the potential to be low-cost provided the array architecture is designed for production using commercially available manufacturing processes. Most modern radar antennas employ some form of nulling to reduce sidelobes in key steering directions. For a transmit AESA the most cost effective implementation is to use phase only to steer the m ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  6. Ceramic Matrix Composite Fins and Nosetips for Gun-Launched Projectiles

    SBC: ULTRAMET            Topic: SCO182003

    Boeing Defense Systems is developing a guided hypervelocity projectile (HVP) and associated integrated launch package assembly. The nosetip and fixed and rotating fin components present particular challenges due to the high aeroheating and dynamic pressure loads and associated temperatures, thermal shock, and oxidizing conditions. Low drag requires sharp tip and edge features on the nose and fins, ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  7. DeepRL Sim-to-Real

    SBC: PIERRE JOHN M LLC            Topic: SCO182006

    PhysicsAI proposes to develop a framework for using deep reinforcement learning to create optimal training data from simulated imagery in order to train machine learning models with improved accuracy, increased robustness, and which support few/zero shot detection for rare objects. Specifically we plan to extend the current state-of-the-art by (1) formulating the task of generating an optimal sim- ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  8. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Arete Associates

    SBC: Arete Associates            Topic: SCO182008

    The Strategic Capabilities Office of OSD is seeking to use machine learning to produce a robust classification capability using ISAR for a relevant radar sensor system. Areté Associates proposes an advanced machine learning approach to perform robust classification with a path towards real-time classification performance. The proposed approach employs a robust method to generate a valid, balanc ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  9. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Toyon Research Corp.

    SBC: TOYON RESEARCH CORPORATION            Topic: SCO182008

    Toyon Research Corp. proposes to develop innovative algorithms to perform automatic target detection (ATR), localization, classification, and sub-classification of maritime targets in ISAR imagery. The proposed algorithms are based on a careful analysis of reflection-mode ISAR imaging systems that aims to address complications that are unique to the images produced in this modality, such as poor r ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
  10. Maritime Target Classification from Inverse Synthetic Aperture Radar (ISAR) Using Machine Learning/Electromagnetic Systems, Inc.

    SBC: ELECTROMAGNETIC SYSTEMS, INC.            Topic: SCO182008

    EMSI proposes to demonstrate the feasibility of extending our machine-learning-based SAR classifiers to provide real-time high confidence maritime target classification from ISAR data collected and processed onboard airborne ISR platforms. To this end, we will modify our classifier architectures to accommodate target motion and ISR platform constraints, simulate realistic ISAR data sets, and deter ...

    SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense
US Flag An Official Website of the United States Government