Improved Magnetic Gradiometers for Unmanned Underwater Vehicles
Abstract
The Office of Naval Research s (ONR) Ocean Battlespace and Expeditionary Access Department (Code 32) explores science and technology in the areas of oceanographic and meteorological observations, modeling, and prediction in the battlespace environment for detecting and neutralizing of mines in both the ocean and littoral environment. In preparation for these Multi-Domain Operations the U.S. Navy requires more sensitive tools to detect intrusions into secure coastal facilities and littoral areas. This includes the detection of low magnetic signature vessels and buried and proud sea mines. The ability to detect these targets with recently developed low cost, low power consumption, high sensitivity solid state magnetics sensors integrated into unmanned underwater vehicles (UUVs) willprovide the Navy with enhanced capability, particularly in the littoral zone. The University of Southern Mississippi s Roger F. Wicker Center for Ocean Enterprise, located at the Port of Gulfport, MS has been researching and testing advanced magnetic sensor designs, and on-board processing to create agnostic magnetic and geophysical sensors to better predict conditions and execute maneuvers in littoral zones faster and more accurately. This includes mapping areas to detect proud and buried mines. During the period of performance different magnetic gradiometer configurations will be tested to determine the ideal sensor configuration for detection classification, and localization (DCL) of low/medium/high metallic targets over a range of environmental conditions and platform noise. We will develop best practices for calibration and vector data construction from total field measurements. For the Automatic Target Recognition (ATRs) algorithms, the targets will be modeled as ellipsoids or as finite length cylinders with given aspect ratios, volume, and magnetization. Magnetization can be estimated reliably using shape parameters of the target, the known magnetic susceptibility of the material such as steel, and the known solutions of self-demagnetization factors. These DCL measurements will help quantifyenvironmental effects on magnetic sensor performance for various gradiometer configurations at the CUBEnet site. This includes estimates of small UUV platform noise, and signal to noise as functions of range, bearing, and height. The inversions to determine the target locations and parameters, such as total magnetic moment, aspect ratio, and orientation will be formulated as a nonlinear least-squares parametric inversions using both the ellipsoid and cylindrical representations. As more in-water data is collected the modeling & simulation capabilities will be finalized, tested, and we will explore sonar fusion and the implications of the novel onboardenhanced navigation capabilities inherent to the vector data. Because the data processing, modeling, and ATR algorithms are very similar for gravity, we can rapidly develop and test these in an operational environment as well. In the last year of the project, we will transition the training algorithms that have developed with our academic partners at Colorado School of Mine s Center for Gravity and Magnetics, and at Jackson State University s Department of Electrical Engineering. This includes (1) Expanded Reality Training for UUV Magnetic Sensor development; and (2) Expanded Reality Training for Magnetic Modeling, Simulation, for UUV sensor integrations and operations. At the end of the project, we will have determined the best magnetic sensor, gradient configurations, and automated processing algorithms for Navy UUV missions. The prototype software algorithms and hardware will be transitioned to ONR and NSWCPanama City.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2023
- Source ID
- N000142312785
Entities
People
- Jason Mckenna
Organizations
- Office of Naval Research
- United States Navy
- University of Southern Mississippi