<p>There is a need to remotely measure the full phase and amplitude information of small-scale acousto-seismic vibrations in order to detect the presence of buried objects (e.g., tunnels, etc.), or for other purposes. This remote sensing information may need to be collected with a large area coverage rate and at a safe standoff distance. To accomplish this, we have implemented a shearographic imaging system that incorporates phase stepping in a novel way, automatically separating random speckle noise from surface motion, without requiring an intermediate unwrapping step. This method, which we call surface-phase-resolved shearography, is especially effective for very low-amplitude motions that generate less than one light-wavelength of phase change. In laboratory studies, we have demonstrated sensitivity of two nanometers RMS with 532-nm-wavelength light.</p>
BAE Systems Sensor Systems Identification & Surveillance (IS) has developed, under contract with the Office of Naval
Research, a multispectral airborne sensor system and processing algorithms capable of detecting mine-like objects in the
surf zone and land mines in the beach zone. BAE Systems has used this system in a blind test at a test range established
by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD) at Eglin Air Force Base. The airborne and
ground subsystems used in this test are described, with graphical illustrations of the detection algorithms. We report on
the performance of the system configured to operate with a human operator analyzing data on a ground station. A
subsurface (underwater bottom proud mine in the surf zone and moored mine in shallow water) mine detection capability
is demonstrated in the surf zone. Surface float detection and proud land mine detection capability is also demonstrated.
Our analysis shows that this BAE Systems-developed multispectral airborne sensor provides a robust technical
foundation for a viable system for mine counter-measures, and would be a valuable asset for use prior to an amphibious
Optical systems designed for some defense, environmental, and commercial remote-sensing applications must simultaneously have a high dynamic range, high sensitivity, and low noise-equivalent contrast. We have adapted James Janesick’s photon transfer technique for characterizing the noise performance of an electron multiplication CCD (EMCCD), and we have developed methods for characterizing performance parameters in a lab environment. We have
defined a new figure of merit to complement the traditionally used dynamic range that quantifies the usefulness of EMCCD imagers. We use the results for EMCCDs to predict their performance with hyperspectral and multispectral imaging systems.
The Littoral Airborne Sensor, Hyperspectral (LASH) system is a stabilized, hyperspectral pushbroom sensor capable of high-resolution imaging. We have implemented a sub-pixel detection algorithm based on stochastic mixing models and integrated this with the LASH hardware/software system for real-time operation and detection. Initial field tests have demonstrated reliable detection of high contrast targets down to the 30% sub-pixel level with false alarm rates less than ~ 10<sup>-7</sup>. The LASH sensor system thus provides a powerful tool for detecting small targets over large search areas, making it a valuable tool for search and rescue and a wide range of other applications.
The shallow water and surf zone (SZ) regions are one of the more difficult environments currently being addressed in littoral mine counter measure (MCM) strategies, yet they are also critical regions for MCM with respect to military breaching tactics. The difficulties in optical remote sensing of the SZ lie mostly in the problem of clutter, which includes transient wave glint, foam patches, turbidity, and detritus. The problem is compounded by the refractive distortion of the small targets (mines and barriers) in these shallow waters. We have adopted several strategies for dealing with clutter rejection in the SZ. The first is a strictly statistical approach to clutter rejection, which is computationally efficient and mathematically simple. The second of these leverages hyperspectral algorithms used for the detection of submerged targets in deep water, wherein the glint is subtracted from the scene prior to image segmentation and anomaly detection. The second method, while more mathematically mature, does not appreciably increase the computation time and provides startlingly better results.