Sparsity-driven multistatic ISAR image reconstruction

The conventional, monostatic way of producing inverse synthetic aperture radar (ISAR) images leaves the user with significant problems in the image interpretation. An ISAR image is the estimate of a two-dimensional (2D) projection of the target’s three-dimensional (3D) reflectivity distribution. The image projection plane (IPP) is usually unknown. To recognise a target, e.g. for non -cooperative identification (NCI), the image (or features extracted from the image) has to be compared against a database that contains all possible projections of all possible targets. Obviously, the creation of such databases is very cumbersome and in fact one of the main reasons why automatic NCI has not found widespread application yet. Chapter Contents: • 7.1 Constraints • 7.1.1 Spatial decorrelation • 7.1.2 Foreshortening effect • 7.2 Problem formulation • 7.3 Reconstruction • 7.4 A simulated example • 7.5 Experimental results • 7.6 Conclusion • References.