Low Size, Weight, Power, and Cost (SWAP-C) Magnetic Anomaly Detection (MAD) System
Navy SBIR 2015.2 - Topic N152-117
ONR - Ms. Lore-Anne Ponirakis - loreanne.ponirakis@navy.mil
Opens: May 26, 2015 - Closes: June 24, 2015

N152-117        TITLE:  Low Size, Weight, Power, and Cost (SWAP-C) Magnetic Anomaly Detection (MAD) System

TECHNOLOGY AREAS:  Air Platform, Sensors

ACQUISITION PROGRAM:  PMA-264, FNC SHD-13-05, High Altitude ASW from the P-8 Unmanned Targeting Air System

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 section 5.4.c.(8) of the solicitation. 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:  Leveraging recent advances in miniaturization of magnetometers, develop a low SWAP-C MAD system for use on small UAVs and helicopters.

DESCRIPTION:  Research over the last decade has significantly reduced the Size, Weight, and Power (SWAP) of atomic vapor magnetometers, [1, 2] making these sensors a good match for unmanned Navy vehicles. This topic seeks innovative designs that incorporate such magnetometers into a Magnetic Anomaly Detection (MAD) system, including both the hardware and software to detect, localize, and track a magnetic dipole target from an Unmanned Aerial Vehicle (UAV). Traditionally, MAD systems must account for a variety of noise sources such as sensor noise, platform noise, geomagnetic noise, and movement in gradient fields so this effort must contain additional sensors to remove these noise sources. This MAD system is envisioned to provide a common sensor for use on Tier 1 UAVs as well as being towed from helicopters. The hardware goals are driven by the intended application for small UAVs. As such, the total field magnetometer should be commensurately small: sensor head size <100cc, electronics module <500cc, low-power (<5W total objective), and low-weight (<5 lbs. total). The noise floor should match or improve upon current commercially available sensors at 0.35 pT/rtHz between 0.01-100 Hz with a raw heading error <300 pT, compensated heading error <10 pT (objective), and remove dead zones inherent in traditional total field magnetometer designs.[3] The system should operate in all Earth’s field conditions (roughly 25 µT – 75 µT). Proposals should include the performance of the existing total field magnetometer planned for incorporation into the MAD system and describe modifications that would be needed to meet these performance goals. The cost objective should be less than $10k in small quantities (~10/year). To reduce noise, additional sensors are usually included in a MAD system: a 3-axis vector magnetometer to compensate for platform noise, [4] a 3-axis accelerometer, GPS inputs, and other sensors. These additional sensors should be in-line with an overall compact low-power design, but need not be included in the SWAP parameters above. 

Software should be able to detect, localize, and track a magnetic dipole target using GPS coordinates that are not necessarily straight and level flight. The algorithms should allow for the possibility of geomagnetic noise reduction with an external reference magnetometer. Computer intensive computations such as heading error correction, noise suppression, and MAD algorithms need not be done in the magnetometer and can be done in an external computer.[5] 

PHASE I:  Define a concept for a prototype compact MAD system. Demonstrate a total field magnetometer meeting the 0.35 pT/rtHz noise performance goal at 1 Hz in a bench top system. Include a 3-axis vector magnetometer and demonstrate an ability to compensate heading error. Develop software approaches for magnetic dipole detection and localization. Investigate noise reduction techniques to be implemented in the software and identify the associated hardware components.

PHASE II:  Based upon the Phase I effort, construct a prototype MAD system and a reference magnetometer. Verify the MAD system survives expected test-flight conditions and meets performance goals in Earth’s background field using the reference. Refine the software and integrate it with the hardware. Conduct a flight test to demonstrate the prototype MAD system’s performance against a simulated target.

PHASE III:  This system will be an integral part of the MAD UAV. Work with the UAV Primes to integrate, test and productionize the MAD system. Conduct operational demonstrate of the system’s performance against a relevant target at sea. PMA-264 is the expected transition sponsor of the MAD UAV technology to be deployed on the P-8A for ASW MAD. Tasking would include: additional ruggedization of the system for Fleet use, implementation of cost reduction measures to provide a minimal-cost product for Navy acquisition, and integration of the system onto an ASW vehicle. 


1.     Dmitry Budker & Michael Romalis, “Optical Magnetometry,” Nature Physics 3, 227-234 (2007).

2.     D. Sheng et al., “Subfemtotesla Scalar Atomic Magnetometry Using Multipass Cells,” PRL 110, 160802 (2013).

3.     A. Ben-Kish and M.V. Romalis, “Dead-Zone-Free Atomic Magnetometry with Simultaneous Excitation of Orientation and Alignment Resonances,” PRL 105, 193601 (2010).

4.     S. H. Bickel, “Small Signal Compensation of Magnetic Fields Resulting from Aircraft Maneuvers,” IEEE Transactions on Aerospace and Electronic Systems Vol. AES-15, No.4, July 1979.

5.     Arie Sheinker et al., “Processing of a scalar magnetometer signal contaminated by 1/fa noise,” Sensors and Actuators A 138 105-111 (2007).


KEYWORDS:  Magnetometer; Magnetic Anomaly Detection, Airborne ASW, Sensor, Detection Algorithms, Noise Compensation

TPOC:  Stephen Potashnik

Email:  stephen.potashnik@navy.mil


2nd TPOC:  Bill Gelatka

Email:  william.gelatka@navy.mil


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