The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"Recent work has developed a number of architectures and algorithms for accurately estimating spacecraft and formation states. The estimation accuracy achievable during spacecraft operation depends not only on the algorithm, but also on its implementation. Typically, the algorithm will be implemented on a real-time multi-tasking processor that allocates on-board computational resources to multiple tasks and functions according to some scheduling policy. The processor's task scheduler may induce delays that were unaccounted for at design-time and may sometimes preempt estimation tasks in favor of other tasks. Hence, estimation accuracy and in general the performance of any embedded algorithm can be significantly lower than expected during execution. The goal of this project is to develop distributed spacecraft state estimation algorithms that account for real-time multi-tasking processor and other implementation related resource constraints. We bring together modeling techniques from multi-class queuing, well-known Kalman filtering techniques and recent advances in embedded systems to develop an innovative co-design framework for the design of embedded state estimation algorithms and software. During the proposed effort, we will design, implement and evaluate estimation algorithms on a network of real-time processors or hardware emulations of processors on-board formation spacecraft. ","releaseStatus":"Released","status":"Completed","viewCount":801,"destinationType":[],"lastUpdated":"01/27/25","favorited":false,"detailedFunding":false,"projectContacts":[],"programContacts":[],"leadOrganization":{"organizationId":4946,"organizationName":"Jet Propulsion Laboratory","acronym":"JPL","organizationType":"FFRDC_2fUARC","city":"Pasadena","stateTerritoryId":59,"stateTerritory":{"abbreviation":"CA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"California","stateTerritoryId":59,"isTerritory":false},"country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"zipCode":"91109","projectId":6026,"projectOrganizationId":35852,"organizationRole":"Lead_Organization","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"Lead Organization","organizationTypePretty":"FFRDC/UARC"},"otherOrganizations":[{"organizationId":4946,"organizationName":"Jet Propulsion Laboratory","acronym":"JPL","organizationType":"FFRDC_2fUARC","city":"Pasadena","stateTerritoryId":59,"stateTerritory":{"abbreviation":"CA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"California","stateTerritoryId":59,"isTerritory":false},"country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"zipCode":"91109","projectId":6026,"projectOrganizationId":35852,"organizationRole":"Lead_Organization","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"Lead Organization","organizationTypePretty":"FFRDC/UARC"},{"organizationId":4445,"organizationName":"Scientific Systems Company, Inc.","organizationType":"Industry","city":"Woburn","stateTerritoryId":30,"stateTerritory":{"abbreviation":"MA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"Massachusetts","stateTerritoryId":30,"isTerritory":false},"country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"zipCode":"01801","dunsNumber":"859244204","uei":"C12TQVKF5413","cageCode":"0KT97","congressionalDistrict":"Massachusetts 05","projectId":6026,"projectOrganizationId":16299,"organizationRole":"Supporting_Organization","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"Supporting Organization","organizationTypePretty":"Industry"}],"primaryTx":{"taxonomyNodeId":11267,"taxonomyRootId":8817,"parentNodeId":11265,"code":"TX10.1.2","title":"State Estimation and Monitoring","description":"State estimation and monitoring technologies estimate internal and external states from raw or processed inputs generated by multiple sensors/instruments, ascertainment, and continual comparison to expected states.","exampleTechnologies":"Pose estimation for a rover, pose estimation for an in-space robotic-assembly arm, velocity estimation for an aerial vehicle, oxygen-level estimation and monitoring, battery health-state estimation, wind-speed estimation for a balloon explorer, tools that assess data validity and manage uncertainty","level":3,"hasChildren":false,"selected":false,"isPrimary":true,"hasInteriorContent":true},"primaryTxTree":[[{"taxonomyNodeId":11264,"taxonomyRootId":8817,"code":"TX10","title":"Autonomous Systems","level":1,"hasChildren":true,"selected":false,"hasInteriorContent":true},{"taxonomyNodeId":11265,"taxonomyRootId":8817,"parentNodeId":11264,"code":"TX10.1","title":"Situational and Self-Awareness Technologies","description":"Situational and self-awareness technologies interrogate, identify, and evaluate both the state of the environment and the state of the system. Examples include artificial neural networks (including deep learning), unsupervised learning, supervised learning, reinforcement learning, feature learning, and support vector machines.","level":2,"hasChildren":true,"selected":false,"hasInteriorContent":true},{"taxonomyNodeId":11267,"taxonomyRootId":8817,"parentNodeId":11265,"code":"TX10.1.2","title":"State Estimation and Monitoring","description":"State estimation and monitoring technologies estimate internal and external states from raw or processed inputs generated by multiple sensors/instruments, ascertainment, and continual comparison to expected states.","exampleTechnologies":"Pose estimation for a rover, pose estimation for an in-space robotic-assembly arm, velocity estimation for an aerial vehicle, oxygen-level estimation and monitoring, battery health-state estimation, wind-speed estimation for a balloon explorer, tools that assess data validity and manage uncertainty","level":3,"hasChildren":false,"selected":true,"hasInteriorContent":true}]],"technologyOutcomes":[],"libraryItems":[],"states":[{"abbreviation":"CA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"California","stateTerritoryId":59,"isTerritory":false},{"abbreviation":"MA","country":{"abbreviation":"US","countryId":236,"name":"United States"},"countryId":236,"name":"Massachusetts","stateTerritoryId":30,"isTerritory":false}],"endDateString":"Jul 2007","startDateString":"Jan 2007"}}