SBIR/STTR Research Award

Identification and classification of small-UAS in the msec range

Award identifier 929adb7f60139a0cc2262cda8c0d7fa9b8a339562a9435057b012f559c8fa0a1Awarding agency Department of Defense · Air Force

Award amount

$103,608

Program and phase

STTR · Phase I

Award year

2025

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Award details

Awarding agency
Department of Defense
Branch
Air Force
Recipient company
Atolla Tech, Inc.
Proposal award date
2025-01-09
Contract end date
2025-04-17
UEI
JSH5ZW41SGX6
Solicitation number
X24.E
Topic code
AFX24E-TPCSO1

Research abstract

Atolla Tech's innovative system, originally designed for the detection and identification of insects in flight, has been meticulously adapted for a more critical application – base defense in military operations. Our system stands out due to its optimization in Size, Weight, Power, and Cost (SWAP-C), making it uniquely suited for integration into existing defense infrastructures.The core of our technology is a sophisticated LiDAR system paired with advanced software analytics, specifically tailored to provide a continuous and comprehensive assessment of airspace. This dual approach of integrating with radar systems allows for early detection of potential threats, while our LiDAR and software ensure precise identification and classification of Unmanned Aerial Systems (UAS). What sets our system apart is the ability to make rapid decisions based on accurate data, a critical need in high-stakes defense scenarios. This is achieved through the integration of mitigation strategies using the data captured by Atolla sensors and the subsequent analysis by our Machine Learning (ML) algorithms.Atolla’s identification algorithm represents a breakthrough in UAS detection. By analyzing wing beat frequency and flight behavior, we can accurately identify and classify UAS. This process involves a detailed waveform analysis in both time and frequency domains, allowing us to ascertain vital characteristics such as the UAS’s size, body reflectance parameters, and flight patterns. Furthermore, our algorithm's ability to analyze the spatial movement over time (defined as flight behavior) enhances its capability in identifying UAS accurately.A key feature of our system is its effectiveness in counter-surveillance operations, particularly against swarm threats. The algorithm’s ability to pinpoint the lead drone in a swarm is instrumental in mitigating such threats. Additionally, our technology can distinguish between friendly and unfriendly drones, an essential feature for ensuring security in military operations.The integration of Atolla Tech's system into military defense strategies offers a significant enhancement in airspace security. Our approach not only increases the accuracy of threat detection and classification but also significantly reduces response times, thereby improving the overall efficiency of military operations. This technological advancement positions Atolla Tech as a leader in innovative defense solutions, offering a system that combines advanced detection capabilities with rapid, data-driven decision-making processes.

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.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

7 SBIR/STTR records share this UEI (2019–2025). Reported award amounts total $1,908,818. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Agriculture

Agency intelligence

Department of Defense

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