Spatially Diverse ISAR Imaging for Classification Performance Enhancement

Spatially Diverse ISAR Imaging for Classification Performance Enhancement One popular approach to the problem of Non-Cooperative Target Identification is the use of 2D Inverse SAR images. Methods to successfully identify a target include the comparison of a set of scattering centers in the ISAR image to a database or the estimation of target dimensions. While working well in theory, these techniques face major difficulties in practice. In the conventional case of a monostatic radar, visibility of scattering centers varies with the target aspect angle due to fading. In this paper we examine that the visibility of scattering centers can be improved by incoherent addition of images from spatially distributed radars. The main focus lies in the description and results of a multistatic ISAR experiment carried out at Fraunhofer FHR. We display theoretically derived bistatic synchronization errors in a practical system and formulate additional multistatic synchronization requirements, necessary to add up the images.