SBIR/STTR Research Award

Decentralized Cooperative Navigation for Small Unmanned Aerial Vehicles in GPS-denied Environments

Award identifier f054b655e1c4a25e43fca1a7d6e195b19e7a4d520fb7d95929033e8a1559d5cbAwarding agency National Aeronautics and Space Administration

Award amount

$124,999

Program and phase

SBIR · Phase I

Award year

2018

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Aeronautics and Space Administration
Branch
Not reported
Recipient company
OPTIMAL SYNTHESIS INC.
Proposal award date
2018-07-27
Contract end date
2019-02-15
UEI
REAUM5F2AM94
Solicitation number
SBIR_18_P1
Topic code
A2

Research abstract

The use of small unmanned aerial vehicles (SUAVs) for civilian as well has military tasks, has been expanding steadily over the years. In this regard, cooperation and interoperability amongst multiple SUAVs has been seen as a key direction of future research by National Aeronautics and Space Administration (NASA). A central challenge in the cooperative navigation using multiple SUAVs is that they often have to operate in GPS-denied environment due to GPS jamming and spoofing or due to the unavailability of any external sources such as georeferencing, for navigation updates for long periods of time. An approach to address this problem is to employ cooperative navigation algorithms by which multiple SUAVs derive better estimates of their location using ownship navigation sensors, in conjunction with navigation data derived from other SUAVs in the vicinity. This proposal advances the development of decentralized cooperative navigation (DCN) algorithms that can improve the navigation performance of multiple SUAVs in GPS-denied environments. The proposed algorithm will tackle the challenges such as communication range and bandwidth limits, relative measurement sensor range and field of view limit, heterogeneous sensor systems and scalability with respect to the number of SUAVs. The Phase I work will provide proof-of-concept for the proposed DCN methodology using simulations. In Phase II, a working prototype will be developed and will be tested using hardware-in-the-loop simulations. The outcome of the research would be a technology for multivehicle cooperative navigation in GPS-denied and GPS-weakened environments.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

102 SBIR/STTR records share this UEI (1994–2020). Reported award amounts total $28,307,929. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Aeronautics and Space Administration, Department of Defense

Agency intelligence

National Aeronautics and Space Administration

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.