Inverse synthetic aperture radar (ISAR) imaging techniques based on indoor near field backscattering measurements turns out to be a powerful tool for diagnostic purposes in radar cross-section (RCS) reduction and for deriving RCS target models, viable for radar systems operating at larger distances, e.g. under far field conditions. This paper presents an advanced 3-D imaging approach, where in addition to the turntable rotation the antenna is moved along a linear path chosen in accordance with the geometry of the target and the aspect angle of interest. For reconstructing the reflectivity distribution a configuration-specific grid of spatial sampling points is employed which reduces the complexity of determining correct values for the scattering amplitudes. The reflectivity distribution reproduces the backscattering seen from an antenna moved along a finite surface (synthetic 2-D-aperture) in the scattering near field of the target, but is to be used to model backscattering for antennas at larger distances, e.g. in the far field. Therefore, the feasibility of this approach is discussed with respect to different applications, i.e. for the diagnostic of RCS reduction and for deterministic or statistical RCS models. Results obtained for a car as X-band radar target are presented in order to verify the features of the imaging system.

Automatic target detection (ATR) depends on the surrounding clutter as well as on the target signatures. Swiss DoD has established a measurement-platform in the W-Band frequency frame to generate the necessary data . The wavelength of the W-Band is much smaller than the target dimension and the footprint of the antenna does not illuminate the entire target. This has the result, that the actual echo-signal correlates strongly to the view angle. The signature of a target is so complex for any kind of evaluation, that it is necessary to create a statistical model with virtual scatters. As an example this model can be integrated in simulations of smart ammunition effectiveness.With data of a statistical model it is possible: -to evaluate the object according its RCS.-to create the necessary camouflage-precaution against radar-seekers and check there efficiency.-to calculate detection probabilities of a target in different clutter conditions. -to identify strong reflectors and thereby reduce the RCS value of the target.

This paper presents two different test methods for camouflage layers (CL) like nets or foam based structures. The effectiveness of CL in preventing radar detection and recognition of targets depends on the interaction of CL properties as absorption and diffuse scattering with target specific scattering properties. This fact is taken into account by representing target backscattering as interference of different types of GTD contributions and evaluating the impact of CL onto these individual contributions separately. The first method investigates how a CL under test alters these individual scattering contributions and which "new" contributions are produced by "self-scattering" at the CL. This information is gained by applying ISAR imaging technique to a test structure with different types of scattering contributions. The second test method aims for separating the effects of absorption and "diffuse scattering" in case of a planar metallic plate covered by CL. For this, the equivalent source distribution in the plane of the CL is reconstructed from bistatic scattering data. Both test methods were verified by experimental results obtained from X-band measurements at different CL and proved to be well suited for an application specific evaluation of camouflage structures from different manufacturers.

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