A set of images generated by multiple passes over the same area can be coherently integrated by this technology developed by LLNL researchers. The primary difficulty with coherently combining different passes is registering the images obtained from each pass, particularly if a pass only partially covers a given area.
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Technology Portfolios
LLNL’s novel approach utilizes a number of techniques to improve reconstruction accuracy:
LLNL researchers have developed a lightweight drone-based GPR array that when flown over a surface with laid and/or buried objects could image the field of view and be able to detect targets and discriminate them from clutter. The imaging method employs a modified multi-static architecture to provide the highest signal to noise with the lowest system weight, making it ideal for airborne or…
This technology uses three different frequency bands to create intensity maps of returned signals. Signals have traditionally been displayed as raw return data. The intensity of the return is represented by level of brightness. Assignment of a scalar value for intensity is used to determine the brightness of the image. In this technology, each frequency is given a designated primary color…
LLNL pioneered the use of tomographic reconstruction to determine the power density of electron beams using profiles of the beam taken at a number of angles. LLNL’s earlier diagnostic consisted of a fixed number of radially oriented sensor slits and required the beam to be circled over them at a fixed known diameter to collect data. The new sensor design incorporates annular slits instead,…
LLNL has developed a wide band (WB) ground penetrating radar (GPR) technology to detect and image buried objects under a moving vehicle. Efficient and high performance processing algorithms reconstruct images of buried or hidden objects in two or three dimensions under a scanning array. The technology includes a mobile high-performance computing system allowing GPR array sensor data to be…