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.

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…

The LLNL method for optimizing as built optical designs uses insights from perturbed optical system theory and reformulates perturbation of optical performance in terms of double Zernikes, which can be calculated analytically rather than by tracing thousands of rays. A new theory of compensation is enabled by the use of double Zernikes which allows the performance degradation of a perturbed…

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…