Submarine Identification by Magnetic Anomaly Recognition

To address the Navy’s need for a system that uses existing magnetometer sensors and an open-architecture computing module to process sensor data and conduct data fusion for classification of the detected target (submarine) on board rotorcraft, Intellisense Systems, Inc. (Intellisense) proposes to develop a new Submarine Identification by Magnetic Anomaly Recognition (SIMAR) system, based on the novel algorithm for data processing while utilizing quantum magnetometer sensors. Specifically, the innovation in the analysis of spectrally (frequency) filtered anomaly components and compensation of rotorcraft maneuvers will enable the SIMAR system to process sensor data and conduct data fusion for classification of the detected target (submarine) on board rotorcraft. As a result, this SIMAR system provides real-time data signal-processing to allow the detection, classification, localization, and tracking of underwater objects such as frontline submarines, which directly address the U.S. Navy Air Anti-Submarine Warfare Systems Program Office (PMA-264) requirements for the detection of mobile submerged targets with the identification of target course, speed, and depth, target length and diameter, propulsion screw turn rate and number of blades, as well as submarine sail length and location to define the submarine type. In Phase I, Intellisense will demonstrate the feasibility of SIMAR by the conceptual design of real-time, open-architecture software signal processing algorithms to achieve classification of underwater objects using commercial off-the-shelf magnetometer sensors onboard rotorcraft. The Phase I effort will include prototype plans to be developed under Phase II, a white paper of the developed or implemented theory, and a complete description of Phase I results. In Phase II, Intellisense plans to develop a prototype operating with commercial magnetometer sensors and SIMAR open-architecture software, perform algorithm testing and performance validation using simulated processed signals and actual data, refine the software, and demonstrate the system classification performance. Then, Intellisense will conduct a flight test to demonstrate the prototype’s capability for classification of underwater objects against a target of opportunity. The prototype will be delivered to the government for use as a laboratory demonstration model.