We propose a new active broadband electromagnetic (EM) sensor to detect and classify naval mines buried in the littoral. The sensor will work like an underwater metal detector, but it will operate at multiple programmable frequencies suitable to a given littoral environment. Once it detects a potential target, the sensor will interrogate the target and measure its spectral responses (inphase and quadrature) over the entire operating bandwidth. The sensor will then compare the measured spectrum with a library of spectra stored for mines that are known or presumed to occur in the survey area. The process will generate a rank-ordered list of spectral matches. As the sensor finds new mines at a site, it can expand its spectral library - a "learn as you go" approach. The proposed active EM sensor can be used as a "confirmation sensor" when it is integrated with other sensors such as passive magnetometers and sonars. A mathematical framework will be developed to interface this data with fusion algorithms being pursued for buried minehunting. In addition, the sensor will serve in a dual role to simultaneously measure the conductivities of the seawater and bottom sediment, which can be used to derive sediment density and porosity, providing important environmental data for mine warfare. Target classification based on the spectral fingerprints is called Electromagnetic Induction Spectroscopy or EMIS. It is known that an EMIS spectrum depends on the objects shape and metal compositions in terms of electrical conductivity and magnetic permeability. Apart from a possibility of direct detection of explosives, EMIS is the only rigorous, physics-based phenomenology for identifying buried mines. The EMIS algorithms, validated for land mines, will be modified for the classification of buried sea mines to provide computer-automated target recognition. This proposal addresses developments of both sensor hardware and EMIS-based software to solve the buried naval mine detection and classification problem.
Benefits: It has been well known that the high false alarm rate is the main factor that complicates naval mine warfare. Without discrimination capabilities to reduce the false alarms, good detectors alone will not be able to solve the problem. Since the majority of resources is currently wasted for dealing with benign objects, reduction in the false alarm rate would result in huge savings in cost and speed. The EMIS concept has far-reaching implications in the general target classification arena such as identifying hidden weapons at a checkpoint.
Keywords: Electromagnetic induction, Frequency-domain EM sensor, Naval mines, EMIS, Target classification
