Part of the DoW SBIR/STTR FY27 Release 2 topic list. Browse all 83 topics by industry or service.
Topic DON27BZ02-NV014 from the DoW SBIR 2027 BAA, Release 2. Pre-release now; proposals due January 6, 2027, 12:00 PM ET.
Quick answer
DON27BZ02-NV014 is a Department of the Navy SBIR topic seeking an autonomous Anti-Submarine Warfare (ASW) reasoning agent that fuses acoustic detections with non-acoustic maritime and environmental data to produce explainable contact assessments and sensor-tasking recommendations on an Unmanned Surface Vehicle. It follows a standard Phase I then Phase II path. Proposals are due January 6, 2027, 12:00 PM ET.
Solicitation at a glance
- Topic number: DON27BZ02-NV014
- Official title: Autonomous Multi-Intelligence Acoustic Reasoning Agent for Anti-Submarine Warfare
- Agency: Department of the Navy
- Program: SBIR (DoW SBIR 2027 BAA, Release 2)
- Award type: Phase I (see topic text for Phase II)
- Award amount: Phase I base up to $200,000 plus an option up to $115,000. Source: Navy Release 2 instructions in DSIP.
- CMMC level: Level 2 (Self)
- ITAR: No
- Technology areas: None
- Pre-release (direct TPOC contact allowed): November 4 to December 2, 2026, 8:00 AM ET
- Opens in DSIP: December 2, 2026, 8:00 AM ET
- Proposals due: January 6, 2027, 12:00 PM ET
- Official source: DSIP Topics app (search DON27BZ02-NV014)
BW&CO's take
What the Department of the Navy wants
ASW today depends on trained operators who interpret passive narrowband, broadband, DEMON, and other acoustic products while mentally fusing bathymetry, sound-speed data, AIS, tracks, and expected target behavior. That is difficult to scale across persistent unmanned systems with intermittent communications. The Navy wants an agent that ingests heterogeneous acoustic detections, correlates them with the common operating picture, reasons over acoustic propagation, handles confusers such as shipping, fishing, and biologics, and maintains explainable track and classification hypotheses over time. It should not be only a single-sensor classifier. Phase II demonstrates prototype software in simulation or replay and delivers a transition package with APIs and model-card documentation.
Who is a good fit
- An existing multi-source sensor fusion or tracking architecture you can describe as the baseline for the ASW fusion design
- Underwater acoustics and propagation modeling expertise, including sound-speed profiles, bathymetry, and clutter or reverberation
- Explainable multi-hypothesis tracking and classification with calibrated confidence
- Autonomy software built for constrained compute, power, and communications on unmanned vessels
Watch-outs
- Submissions must describe prior sensor fusion development that will serve as the baseline. A proposal without that history is weaker.
- The topic says the system should demonstrate multi-source temporal reasoning that explains its assessments and should not be a single-sensor classifier only.
- Phase II work and data may become classified. The contractor must be U.S. owned and operated with no foreign influence and able to acquire and maintain a Secret facility clearance and personnel clearances.
- The topic requires CMMC Level 2 (Self). It is not marked as ITAR-restricted in the topic metadata.
Think your company fits DON27BZ02-NV014? Talk with BW&CO before the January 6 deadline.
Plan Your DON27BZ02-NV014 Submission
Official topic text (verbatim from DSIP)
The text in this section is copied word for word from the official DSIP topic as published on November 4, 2026. DSIP is the official source and topics can be amended. Always confirm the current version at dodsbirsttr.mil before you submit. Our commentary above is BW&CO's interpretation, not Government guidance.
Title
Autonomous Multi-Intelligence Acoustic Reasoning Agent for Anti-Submarine Warfare
Objective
Develop an autonomous Anti-Submarine Warfare (ASW) reasoning agent that fuses passive and active acoustic detections with non-acoustic maritime situational data, environmental acoustic propagation context, and platform/target behavior models to produce explainable contact assessments, track hypotheses, and recommended sensor-tasking actions; and supports deployment on an Unmanned Surface Vehicle (USV) with constrained communications, power, and computing conditions.
Description
The Department of the Navy (DON) seeks development of an autonomous decision-support and reasoning capability for ASW that can reduce dependence on continuous human interpretation of complex acoustic displays and enable future distributed unmanned ASW operations. Current ASW performance is heavily dependent on trained operators who interpret passive narrowband, passive broadband, Demodulation of Noise (DEMON), and other acoustic products while simultaneously incorporating situational knowledge such as geography, bathymetry, Conductivity Temperature and Depth (CTD) data for sound-speed structure, Global Positioning System (GPS), Automatic Identification System (AIS), organic/non-organic tracks, surface traffic, tactical geometry, and expected target behaviors. This human fusion process is effective but difficult to scale across persistent unmanned systems operating at range, under intermittent communications, and in acoustically cluttered environments.
This SBIR topic requests development of an autonomous ASW agent that can ingest heterogeneous acoustic detections and associated confidence measures, correlate them with non-acoustic common operating picture data, reason over environmental acoustic propagation, and maintain multiple explainable track and classification hypotheses over time. The capability should explicitly account for confusers such as merchant shipping, fishing vessels, biologics, own-force and friendly surface ship contributions, reverberation/clutter, and geographically-dependent propagation effects. The resulting system should not be a single-sensor classifier only; it should demonstrate multi-source temporal reasoning that can explain why a contact is assessed as likely submarine, non-submarine, ambiguous, or requiring additional sensing. The approach should be modular and compatible with Navy acoustic processing and performance-prediction workflows, while allowing Navy-provided threat behavior models, environmental data, and acoustic feature streams to be incorporated without redesign. Submissions should include a description of prior sensor fusion development that will serve as a baseline for the proposed ASW fusion architecture.
Work produced in Phase II may become classified. Note: The prospective contractor(s) must be U.S. owned and operated with no foreign influence as defined by 32 U.S.C. § 2004.20 et seq., National Industrial Security Program Executive Agent and Operating Manual, unless acceptable mitigating procedures can and have been implemented and approved by the Defense Counterintelligence and Security Agency (DCSA) formerly Defense Security Service (DSS). The selected contractor and/or subcontractor must be able to acquire and maintain a secret level facility and Personnel Security Clearances. This will allow contractor personnel to perform on advanced phases of this project as set forth by DCSA and ONR in order to gain access to classified information pertaining to the national defense of the United States and its allies; this will be an inherent requirement. The selected company will be required to safeguard classified material during the advanced phases of this contract IAW the National Industrial Security Program Operating Manual (NISPOM), which can be found at Title 32, Part 2004.20 of the Code of Federal Regulations.
Phase I
Develop a concept for the proposed software architecture for an autonomous ASW reasoning agent, including data schemas for acoustic detections, Common Operation Picture (COP)/non-acoustic inputs, environmental context, target-behavior priors, uncertainty representation, and operator-interpretable explanations. Demonstrate proof-of-concept using representative or open acoustic and maritime datasets to demonstrate fusion of passive acoustic features with disparate data features. Prepare a Phase I final report that includes a performance assessment plan that quantitively assesses metrics such as track purity, false-track/alarm suppression, classification confidence calibration, explanation quality, latency, and robustness to missing/degraded inputs.
Phase II
Develop prototype software with implementation capability that should ingest multiple acoustic modalities, correlate acoustic contacts with non-acoustic maritime tracks, maintain multiple hypotheses, and recommend sensor-tasking or unmanned maneuver options to improve classification confidence. Demonstrate the software in simulation or replay using geographically realistic bathymetry, sound-speed profiles, surface traffic, environmental noise, and target/non-target behavior profiles. Include a transition package that documents Application Programming Interfaces (APIs), modular interfaces to Navy propagation/performance-prediction tools, model-card style documentation, training/evaluation data requirements, and a plan for integration with unmanned ASW mission systems. Prepare a Phase III commercialization/transition plan.
Work and/or data used in Phase II may become classified. Please see note in the Description.
Phase III Dual Use Applications
Sensor fusion for acoustic clutter reduction supports seismic surveys of commercial oil prospecting and more general ocean exploration efforts in support of the ocean acoustics National Naval Responsibility. Understanding how to fuse ocean ambient sound in terms of its spatial, temporal, and frequency contributions as well as elucidating information about air and seafloor interfaces will provide a clearer picture of the undersea world where the Navy operates. Commercial dual-use applications may include maritime domain awareness, port and harbor security, offshore infrastructure monitoring, autonomous vessel operations, illegal fishing detection, environmental acoustic monitoring, and marine mammal or vessel-noise characterization.
References
DARPA Tactical Technology Office. “Anti-Submarine Warfare Continuous Trail Unmanned Vessel (ACTUV)/Sea Hunter.” ACTUV | DARPA
Sur, I. et al. “Data-Driven Distributed Common Operational Picture from Heterogeneous Platforms using Multi-Agent Reinforcement Learning.” arXiv, 2024. Data-Driven Distributed Common Operational Picture from Heterogeneous Platforms using Multi-Agent Reinforcement Learning | Arxiv - DeepPaper
Panteli, E., Santos, P. E. and Humphrey, N. “AquaSignal: An Integrated Framework for Robust Underwater Acoustic Analysis.” arXiv, 2025. AquaSignal: An Integrated Framework for Robust Underwater Acoustic Analysis
Shipton, M., Denona, V., Nad, D. and Diamant, R. “ShipEcho -- An Interactive Tool for Global Mapping of Underwater Radiated Noise from Vessels.” arXiv, 2026. [2605.08194] ShipEcho -- An Interactive Tool for Global Mapping of Underwater Radiated Noise from Vessels
Spadon, G., Ferreira, M. D., Soares, A., and Matwin, S. “Unfolding AIS Transmission Behavior for Vessel Movement Modeling on Noisy Data Leveraging Machine Learning.” arXiv, 2022. [2202.13867] Unfolding AIS transmission behavior for vessel movement modeling on noisy data leveraging machine learning
Etter, P. C. “Underwater Acoustic Modeling and Simulation.” CRC Press. Underwater Acoustic Modeling and Simulation: Etter, Paul C.: 9781138054929: Amazon.com: Books
“ISO 18405:2017, Underwater Acoustics — Terminology Edition 1, 2027” International Organization for Standardization. ISO 18405:2017 - Underwater acoustics — Terminology
“National Industrial Security Program Executive Agent and Operating Manual (NISP), 32 U.S.C. § 2004.20 et seq. 1993.” https://www.ecfr.gov/current/title-32/subtitle-B/chapter-XX/part-2004
Keywords
autonomy, software, acoustic, senor fusion, unmanned vehicles, UxS, ocean, Anti-Submarine Warfare, ASW
Frequently asked questions
What is DON27BZ02-NV014?
It is a Department of the Navy SBIR topic to develop an autonomous ASW reasoning agent that fuses passive and active acoustic detections with non-acoustic maritime data, propagation context, and behavior models to produce explainable contact assessments, track hypotheses, and sensor-tasking recommendations, deployable on a USV.
When is DON27BZ02-NV014 due?
Proposals are due January 6, 2027, 12:00 PM ET. DSIP pre-release began November 4, 2026, and direct contact with the topic authors is allowed only until the topic opens on December 2, 2026, 8:00 AM ET. After that, questions go through DSIP Topic Q&A.
Is this a Phase I or Direct-to-Phase II topic?
It is a standard Phase I topic. Phase I delivers a software architecture concept with data schemas and a proof of concept on representative or open acoustic and maritime datasets. Phase II develops prototype software demonstrated in simulation or replay.
What metrics should the performance assessment plan cover?
The Phase I report must include a plan that quantitatively assesses metrics such as track purity, false-track and false-alarm suppression, classification confidence calibration, explanation quality, latency, and robustness to missing or degraded inputs.