Improved 3D ISAR Using Linear Arrays

Inverse synthetic aperture radar (ISAR) has been developed to image non-cooperative targets, so they can be classified by an operator or a more advanced classification system. Three dimensional (3D) ISAR is an extension that produces ‘point clouds' of non-cooperative maritime targets and offers the potential for improved target classification. As element-level arrays become more mainstream, it is possible to exploit the extra channels to improve target imaging. In this paper, we consider a radar system comprising a number of spatial antennas. The estimated target features such as the length, width and height can be determined by the interferometric phase of scatterers identified in an ISAR image. We propose a technique that exploits uniform linear arrays to improve the accuracy of the phase estimates and hence produce better feature estimates. The new approach is demonstrated using a high fidelity ISAR simulation and tested with two different 3D ISAR techniques.