N251-016 TITLE: Expendable Sonobuoy-Launched Unmanned Aerial Vehicle for ASW Cued Search, Detection, Tracking, and Classification

OUSD (R&E) CRITICAL TECHNOLOGY AREA(S): Trusted AI and Autonomy

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.

OBJECTIVE: Develop an expendable Tier 1 Sonobuoy Launched Unmanned Aerial Vehicle (SL UAV) that can be launched from a P-8A’s sonobuoy launcher system from high altitude, with a sensitive magnetometer, and capable of deploying an in-water passive acoustic sensor(s) for Anti-Submarine Warfare (ASW) target cued search, detection, localization, tracking, and classification.

DESCRIPTION: The metrics of this development are:

Overall Sonobuoy Launched UAV for ASW Re-Acquire, Tracking, and Classification System Objectives:

1. Packaging: LAU-126A Sonobuoy Launch Container (SLC) or equivalent,
2. SLUAV Weight: Max 39 lb (17.7 kg) (bare, not including the SLC),
3. SLUAV Stowed Dimensions: 4.875 in. (12.38 cm) diameter x 36 in. (91.44 cm) length,
4. Storage: 9 years shelf life,
5. Launch Envelope: Full Sonobuoy production specification,
6. Speed: 70 kts Cruise Air Speed (Threshold),
7. Endurance: 70 min (Threshold),
8. Operational Altitude: 500–2,000 ft (15.24 m–609.6 m),
9. Range: 20 nm LOS (extending to 50 nm),
10. Payload Volume: Greater than 94.4 in.³ (1546.94 cm³),
11. Environment:
1. Temperature – must be able to operate in -20 °C–50 °C,
2. Light Rain such that visibility is greater than 1 nm,
12. Autonomy: Threshold: Fly pre-programmed waypoint tracks and orbits, Objective: Transition to autonomous target tracking as cued by MAD system,
13. On board Processing:
1. AI performance: Not less than 275 TOPS (INT8),
2. Max GPU frequency: Not less than 1.3 GHz,
3. Number of GPU cores: Not less than 2048 CUDA cores and 64 Tensor cores,
4. Number of CPU cores: Not less than 12,
5. CPU frequency: 2.2 GHz,
6. Memory (RAM): Not less than 64 GB.
14. Command and control:
1. Phase I and II: Any,
2. Phase III: UAS Control Segment (UCS) Architecture, and
15. Cost: In final form, < $10,000 in quantities of 100.

Magnetic Anomaly Detection (MAD) System Specific Objectives:

The SL UAV must support MAD with the requirement that the inherent platform motion coupled with the SL UAV & acoustic sensor payload magnetic signature shall not prevent the following performance:

1. Platform magnetic field components will exhibit an amplitude noise spectral density of less than 1 pT/rtHz from DC to 100 Hz.
2. Magnetometer should work in real-world conditions including a dynamic range of +/- 100 µT on each axis, no dead zones, and an accuracy of 1 nT over the temperature range of -0 °C–50 °C.
3. MAD in-air noise level: Threshold: 20 pT/rtHz in 0.01–100 Hz with a raw heading error of

In-Water Passive Acoustic Sensor Specific Objectives:

1. Operating Life: Threshold 60 min; Objective 70 min,
2. Max Operating Depth: Threshold 200 ft (60.96 m); Objective 400 ft (121.92 m),
3. Deployment time: Threshold 120 s; Objective 60 s,
4. Scuttle: Threshold: Automatic based battery life remaining; Objective: Automatic and on- command,
5. Sensor DI: Threshold: omni; Objective: higher gain and/or direction-finding capability,
6. Sensor(s) Frequency Coverage: Threshold: 0.01 Hz–2.5 kHz; Objective: 0.001Hz–25 kHz,
7. Sensor Noise Equivalent: dependent on proposed topology; intent would be to extend contact time (detection range) commensurate with DI and ambient conditions,
8. Data shaping: whitened to environment for reduced uplink bandwidth,
9. Sensor Calibration Accuracy: Threshold: +/-2dB; Objective: +/-1dB,
10. Range: 20 nm LOS (extending to 50 nm).

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 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 NAVAIR 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 an expendable SL UAV supplied with an Area of Uncertainty (AOU) conduct a cued search, detection, localization and classification using MAD and an in-water passive acoustic sensing capability to meet the above requirements. Explicitly state, theoretical, physical, numerical and computational methods employed. Approach for aircraft design and MAD/acoustic operation should be back up with simulated results and proved experimentally on a laboratory environment before proceeding to Phase II. If developing a new aircraft, compare to performance of similar SL UAVS previously developed. Clearly label artificial intelligence/machine learning (AI/ML) methods employed on SL UAV computer. Compare performance with non-linear correlation methods often employed on weak ML neural-networks. MAD detection and classification methods should not be limited to dipole models and must include, but not limited to, harmonic fields. Computational methods should be able to implement data fusion algorithms incorporating different sensor types. Encryption methods for data transmission should also be addressed.

A prototype of the aircraft should be completed by Phase I. This includes structural analysis and flight clearances. Magnetic characterization at magnetometer location should also be completed at different engine speeds. Failure to meet the magnetic noise threshold at the magnetometer location will result on a rejection for a Phase II.

A successful Phase I will be defined on meeting the threshold on the above-mentioned parameters in the structural analysis, simulation, and laboratory testing. Results from the previous should be confirmed by the TPOC, and more analysis/test may be requested by the TPOC as needed. The Phase I effort will include prototype plans to be developed under Phase II.

PHASE II: Based upon the Phase I effort, construct SLUAV MAD + Acoustic ASW System and demonstrate the feasibility of meeting the above requirements on a relevant and operation environment. A successful Phase II effort will culminate with a full-system demonstration of the combined MAD and acoustic capabilities on multiple SL UAVs. The SL UAVs, during this demonstration, should be air launched from a surrogate platform to demonstrate they can unfold, transition into stable flight and communicate. Additionally, the SL UAVs should be subjected to shock loads prior to air launch, these shock loads should replicate the loads the prototype would see from a Cartridge Activated Device (CAD) launcher or pneumatic sono-launcher as close as possible.

A successful Phase II will also measure the ability of the SL UAVs to operate in Swarm, classify and localize targets, and meet the in-flight thresholds defined on the Description.

Work in Phase II may become classified. Please see note in the Description section.

PHASE III DUAL USE APPLICATIONS: Based upon the Phase II effort, on a relevant environment, conduct a Swarm search with SL UAV’s, which includes relevant targets. Effort should detect, track, and classify targets using a combination of both magnetic sensors and acoustic sensors. The SL UAV’s should be air launched from a relevant platform, which satisfy sponsors’ demands.

SL UAV technology, combined with data fusion and processing capabilities, would improve product innovation in the deliverable of products meeting reckoning and detection demand while airborne both in the sea and earth landscape.

REFERENCES:

1. Ash, A. D. "Noise and noise reduction techniques for airborne magnetic measurements at sea [Paper presentation]." International Conference on Marine Electromagnetics, MARELEC, London, United Kingdom, June 23-26, 1997. https://books.google.com/books/about/International_Conference_on_Marine_Elect.html?id=StQjuwEACAAJ

2. Ben-Kish, A. and Romalis, M. V. "Dead-zone-free atomic magnetometry with simultaneous excitation of orientation and alignment resonances." PRL, 105, 193601, November 4, 2010. https://doi.org/10.1103/PhysRevLett.105.193601

3. Clem, T.; Allen, G.; Bono, J.; McDonald, R. J.; Overway, D.; Sulzberger, G.; Kumar, S. and King, D. "Magnetic sensors for buried minehunting from small unmanned underwater vehicles [Paper presentation]." Oceans ’04 MTS/IEEE Techno-Ocean, London, United Kingdom, November 9-12, 2004. https://doi.org/10.1109/OCEANS.2004.1405594

4. Wolf, T.;, Neumann, P.; Nakamura, K.; Sumiya, H.; Ohshima, T.; Isoya, J. and Wrachtrup, J. "A Subpicotesla Diamond Magnetometry." Phys. Rev. X, 5(4), 041001, October 5, 2015. https://doi.org/10.1103/PhysRevX.5.041001

5. Sherman, C. H. and Butler, J. L. "Transducers and arrays for underwater sound (Vol. 4)." New York: Springer, 2007. https://www.worldcat.org/title/transducers-and-arrays-for-underwater-sound/oclc/1042096780&referer=brief_results

6. Defense Counterintelligence and Security Agency. (n.d.). https://www.dcsa.mil/

7. "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: Unmanned; Air Vehicle; UAV; UAS; Magnetic; MAD; Acoustic; Infrasound; Machine Learning; Artificial Intelligence

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