Feature ArticleDetecting, Classifying Mines With Synthetic Aperture Acoustic Tomography
The SSAM system and example imagery showing engravings on a mooring and high-resolution detail of objects at maximum range. The background displays a mirrored high-frequency and broadband image, with subsurface geology evident in the latter. (Photo courtesy of the U.S. Navy)
Synthetic aperture technology originated in the radar community in the mid-20th century and was adapted by the sonar community approximately 20 years later. For some time, SAS was not practical because of the limitations associated with enabling technologies such as underwater platforms, suitable motion measurement instrumentation, accurate motion estimation techniques, and the storage and processing components needed to meet the computational requirements associated with SAS beamforming. This has changed over recent years and SAS systems are now being fielded in a range of military and commercial applications such as geological mapping, telegraph and pipeline surveys, environmental remediation, marine salvage and archeology, and mine countermeasures.
Small Synthetic Aperture Minehunter
Since the 1980s, the U.S. Office of Naval Research has developed advanced SAS systems for detection, localization and classification of mines protection of sea lines of communication and naval operating areas, and support of amphibious operations. The range of activities required by these sensors include: intelligence preparation of the operational environment, search-classify-map (SCM) operations, and reacquisition-identification (RI) of mine-like objects for subsequent neutralization.
Recently developed SAS systems have been designed to operate over a range of wavelengths and aspects. Centimeter-scale wavelengths (with acoustic frequency typically greater than 100 kilohertz) are used for fine-detail imaging of seabed texture and of small man-made objects. Longer wavelengths, which propagate deeper into the sediment volume, are used for imaging and spectroscopic analysis of proud and buried objects.
The Small Synthetic Aperture Minehunter (SSAM), developed by the Naval Surface Warfare Center Panama City Division (NSWC PCD) and the Applied Research Laboratory, Penn State University, is a multiscale design that exploits all of these advantages. It consists of two SAS systems: a high-frequency SAS and a broadband SAS, wherein two separate projectors share a common hydrophone array. The broadband SAS provides detection, classification and localization of scoured and partially buried objects. The SSAM is deployed on a 12.75-inch-diameter Hydroid Inc. (Pocasset, Massachusetts) REMUS 600 AUV, operated by the Woods Hole Oceanographic Institution.
Presently, two generations of the SSAM concept exist, both of which operate in strip-map mode: monostatic and utilizing broadside beams. The first-generation SSAM system was fielded from 2005 through 2009, participating in 11 events and surveying more than 23 square nautical miles of seabed. The second-generation system, SSAMII, has been fielded since 2010 and is designed for hunting proud and heavily scoured objects in shallow-water and nearshore environments. To continue this article please click here.
Dr. Daniel D. Sternlicht is the head of the sensing sciences division at the Naval Surface Warfare Center Panama City Division, which develops advanced sensors and processing for U.S. Navy and Marine Corps missions. He received a Ph.D. in electrical engineering and applied ocean science from the University of California, San Diego, and Scripps Institution of Oceanography.
Jose E. Fernandez is the senior sonar engineer for the sensing sciences division at the Naval Surface Warfare Center Panama City Division. He has worked in the design, testing and data analysis of several sonar systems. Most of his recent work has been related to the development of synthetic aperture sonar technology.
Dr. Timothy M. Marston, a research scientist in the field of signal processing at the Naval Surface Warfare Center Panama City Division, received a Ph.D. in acoustics from Penn State University in 2009. Since 2010, his primary focus has been the development of robust algorithms for synthetic aperture data processing.