USA flag logo/image

An Official Website of the United States Government

Active Broadband EM Detection and Classification of Buried Naval Mines

Award Information

Department of Defense
Award ID:
Program Year/Program:
2004 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
605 Mercury Street Raleigh, NC -
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 2
Fiscal Year: 2004
Title: Active Broadband EM Detection and Classification of Buried Naval Mines
Agency / Branch: DOD / NAVY
Contract: N00014-03-C-0339
Award Amount: $444,522.00


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 object's 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.

Principal Investigator:

Stephen J. Norton

Business Contact:

Steven Daib
Contract Administrator
Small Business Information at Submission:

605 Mercury Street Raleigh, NC 27603

EIN/Tax ID: 561378871
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No