SBIR/STTR Research Award

SIGnature Management Agent (SIGMA)

Award identifier 931a681d231c868a24b181b7a684a76ba2ba4a0fad5bf861443bb7b58981086dAwarding agency Department of Defense · Navy

Award amount

$140,000

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
STOTTLER HENKE ASSOCIATES, INC
Proposal award date
2020-06-19
Contract end date
2020-12-16
UEI
FFEAH6Z5CK27
Solicitation number
20.1
Topic code
N201-059

Research abstract

USV SIGCON (signature control) consists of enhancing, reducing, manipulating, and directionally controlling all signatures including electromagnetic (EM) and acoustic signatures. USVs will be tasked with a variety of missions from collections to mine clearance, and every situation within every mission demands autonomous, dynamic, real-time onboard SIGCON. This includes the ability to follow International Regulations for Preventing Collisions at Sea (COLREGs)/Rules of the Road and Emissions Control (EMCON) as appropriate. We propose SIGMA (SIGnature Management Agent) to autonomously control signatures on USVs. SIGMA takes in potentially days-old broad guidance from a distant controlling station (e.g., mission objectives, commander’s intent, ROE, etc.) as well as organic and inorganic data (e.g., radar, sonar, AIS, GPS, weather) to appropriately control sensors (e.g., turn off active radar, turn ship, broadcast AIS) and employ techniques (e.g., utilize deceptive lighting, spray mist or chaff). SIGMA utilizes several tried-and-tested artificial intelligence (AI) techniques including Knowledge Engineering (KE), Fuzzy Logic (FL), Behavior Transition Networks (BTNs), and Case-Based Reasoning (CBR). Knowledge Engineering refers to the process of extracting knowledge from subject matter experts, developing a Knowledge Representation (KR), and building a system based on formal and informal facts, rules, and frames. Robert Bergman and Jonathan Vandervelde, who have expert knowledge in Electromagnetic Spectrum Operations (EMSO) and Electronic Warfare (EW), will provide subject matter expertise that will be integrated into SIGMA. Fuzzy Logic captures rules that reference qualitative, inexact, or “fuzzy” values such High/Medium/Low. Behavior Transition Networks create intelligent behaviors by dividing behavior hierarchically into tasks connected by transitions. Finally, Case-Based Reasoning (CBR) attempts to solve the current problem by retrieving a previously encountered similar problem and adapting that problem’s solution to the current situation. In Phase I, we will develop a limited prototype SIGMA and test it using both the Navy-provided data and our in-house simulator. In Phase II, we will build at least two SIGMAs with improved capabilities that meet the Unmanned Maritime Autonomy Architecture (UMAA), and we will integrate them into actual USVs.

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

428 SBIR/STTR records share this UEI (1990–2026). Reported award amounts total $136,164,855. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, Department of Energy, Department of Commerce, National Science Foundation

Agency intelligence

Department of Defense

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