
pmid: 18972656
We introduce a novel synthetic-aperture imaging method for radar systems that rely on sources of opportunity. We consider receivers that fly along arbitrary, but known, flight trajectories and develop a spatio-temporal correlation-based filtered-backprojection-type image reconstruction method. The method involves first correlating the measurements from two different receiver locations. This leads to a forward model where the radiance of the target scene is projected onto the intersection of certain hyperboloids with the surface topography. We next use microlocal techniques to develop a filtered-backprojection-type inversion method to recover the scene radiance. The method is applicable to both stationary and mobile, and cooperative and noncooperative sources of opportunity. Additionally, it is applicable to nonideal imaging scenarios such as those involving arbitrary flight trajectories, and has the desirable property of preserving the visible edges of the scene radiance. We present an analysis of the computational complexity of the image reconstruction method and demonstrate its performance in numerical simulations for single and multiple transmitters of opportunity.
Imaging, Three-Dimensional, Radar, Artificial Intelligence, Image Interpretation, Computer-Assisted, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Algorithms, Pattern Recognition, Automated
Imaging, Three-Dimensional, Radar, Artificial Intelligence, Image Interpretation, Computer-Assisted, Reproducibility of Results, Image Enhancement, Sensitivity and Specificity, Algorithms, Pattern Recognition, Automated
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