In this article we present the realization of an experimental multistatic inverse synthetic aperture radar (M-ISAR) system. The primary focus of this work is to utilize the multistatic geometry to estimate the motion of a maneuvering ground target. We propose solutions to all experimental challenges that go along with such a setup, including hardware development, synchronization, and signal processing. Results from real data show that images of reasonable quality can be obtained without making strong assumptions on the target trajectory. On the basis of these results, benefits and drawbacks of the multilateration approach to motion estimation are discussed, critical elements of the processing chain are highlighted, and phenomenological experience is shared

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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.

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