Pixelated Cadmium Zinc Telluride (CZT) detectors provide the opportunity to perform spectroscopic imaging for
discriminating one radioactive material from another. Although Compton interactions provide a means for imaging high
energy gamma sources, identification of materials emitting lower energy signatures are better suited to collimator
imaging techniques. This paper specifically considers a multiple pinhole method for its simplicity of pinhole focusing
combined with straightforward processing methods for incorporating multiple apertures to reduce photon collection time
while retaining image resolution. Multiple pinhole image detections are combined using an iterative Maximum-
Likelihood Expectation-Maximization (MLEM) synthetic imaging algorithm. To enable subsequent field operations, the
imaging system matrix is computed using an imaging model with adjustable parameters rather than one experimentally
acquired from point sources. The system model includes an object space, a multiple pinhole collimator plane, and a
pixelated detection plane. The modeled object space is implemented in two dimensions to reduce image reconstruction
burden since 3D imaging is not practical for single view stand-off imaging. Focusing is modeled by a function
computing photon trajectory and passage through the pinhole patterned barrier plane. Results show that a MLEM
processed image will achieve resolution approaching that of a single pinhole imaged onto the full detector. The multiple
pinhole advantages of simple implementation with shorter focal lengths combined with the availability of portable CZT
detectors would be useful in short stand-off applications. Work is currently in progress to experimentally quantify spatial
resolution and imaging timelines using an eV Products D-Matrix 4x4 array of pixelated CZT modules.
The methods for the optimization of the magnetoresistive (MR) sensors are to reduce sources of noises, to increase the signal, and to understand the involved fundamental limitations. The high-performance MR sensors result from important magnetic tunnel junction (MTJ) properties, such as tunneling magnetoresistance ratio (TMR), coercivity (Hc), exchange coupling field (He), domain structures, and noise properties as well as the external magnetic flux concentrators. All these parameters are sensitively controlled by the magnetic nanostructures, which can be tuned by varying junction free layer nanostructures, geometry, and magnetic annealing process etc. In this paper, we discuss some of efforts that an optimized magnetic sensor with a sensitivity as high as 5,146 %/mT. This sensitivity is currently the highest among all MR-type sensors that have been reported. The estimated noise of our magnetoresistive sensor is 47 pT/Hz1/2 at 1 Hz. This magnetoresistance sensor dissipates only 100 μW of power while operating under an applied voltage of 1 V at room temperature.
A machine vision system needing to remain vigilant within its environment must be able to quickly perceive both
clearly identifiable objects as well as those that are deceptive or camouflaged (attempting to blend into the background).
Humans accomplish this task early in the visual pathways, using five spatially defined forms of processing. These
forms are Luminance-defined, Color-defined, Texture-defined, Motion-defined, and Disparity-defined. This paper
discusses a visual sensor approach that combines a biological system's strategy to break down camouflage with simple
image processing algorithms that may be implemented for real time video. Thermal imaging is added to increase
sensing capability. Preliminary filters using MATLAB and operating on digital still images show somewhat
encouraging results. Current efforts include implementing the sensor for real-time video processing.
Plastic-Bonded Explosives (PBXs) are a newer generation of explosive compositions developed at Los Alamos National Laboratory (LANL). Understanding the micromechanical behavior of these materials is critical. The size of the crystal particles and porosity within the PBX influences their shock sensitivity. Current methods to characterize the prominent structural characteristics include manual examination by scientists and attempts to use commercially available image processing packages. Both methods are time consuming and tedious. LANL personnel, recognizing this as a manually intensive process, have worked with the Kansas City Plant / Kirtland Operations to develop a system which utilizes image processing and pattern recognition techniques to characterize PBX material. System hardware consists of a CCD camera, zoom lens, two-dimensional, motorized stage, and coaxial, cross-polarized light. System integration of this hardware with the custom software is at the core of the machine vision system. Fundamental processing steps involve capturing images from the PBX specimen, and extraction of void, crystal, and binder regions. For crystal extraction, a Quadtree decomposition segmentation technique is employed. Benefits of this system include: (1) reduction of the overall characterization time; (2) a process which is quantifiable and repeatable; (3) utilization of personnel for intelligent review rather than manual processing; and (4) significantly enhanced characterization accuracy.
Formation structure and relative spacecraft velocities for a multiple baseline single pass IFSAR system are investigated to optimize a composite interferometric observation over several subapertures. Two major system models are developed: (1) relative spacecraft motion, and (2) pixel height measurement variance. Analysis demonstrates that a generalized Keplerian trajectory model with an equal gravity gradient assumption provides sufficient accuracy over typical IFSAR flyby aperture lengths. A pixel height variance model is developed to address issues unique to single pass multiple baseline space-based systems. A bistatic spotlight mode IFSAR system is assumed. Bistatic operation is not necessary, but the reduced future costs of deploying high performance sensor arrays of smaller receiver spacecraft drive the development of this important technology. Modeled noises for the multiple baseline system include internal sensor noise, spatial decorrelation noise, non-parallel ground track (grid rotation) decorrelation noise, and system parameter uncertainties. With expected observation ranges in excess of 500 kilometers, large baselines are required to maximize IFSAR height sensitivity. An analysis of optimal correlation is presented that extends the work of Rodriguez & Martin (1992) to include model uncertainties. Four IFSAR formation scenarios have been investigated. The system trajectory mimics the planned flyby of the Kilauea volcano by the Air Force TechSat 21 multiple spacecraft demonstration. Supposed formations include (1) a free-fall cluster formation, (2) an optimal formation assuming adequate thrust, and (3) a free-fall flyby after optimal initial formation. Results demonstrate pixel height errors at the spotlight aim point to range from 1 to 4 meters over the several 1-second subaperture lengths, and 0.2 to 0.5 meters over the 47-second full aperture length. A fourth scenario investigates performance over a hyperbolic flyby trajectory.