Abstract-The bistatic radar cross section of a dihedral at three different orientations is measured and compared to five scattering predictions-method of moments (MoM), finite integration technique (FIT), shooting and bouncing rays (SBR), and two analytic models-closed-form PO (CPO) and a simplified parametric model. For many applications, accurate predictions in the mainlobe response are of most importance. We show that bistatic CPO and PM predictions have good fit to measured data in the mainlobe and are computationally more efficient than the numerical prediction methods.

Modern remote sensing applications, including radar, require thoughtful consideration of electromagnetic principles for constructing advanced signal processing algorithms for detection, estimation, tracking, imaging and feature extraction. Starting from a generalized picture of the distributed sensing paradigm, this paper presents current efforts at the Radar Instrumentation Laboratory, Air Force Institute of Technology to develop efficient target models for use in integrated imaging and feature extraction algorithms for fully polarimetric synthetic aperture radar (SAR). In continuing the development of anisotropic target models, closed form expressions are presented for canonical objects, and using both simulation and measurement from the Gotcha challenge data, a new and efficient integrated algorithm is demonstrated for finding distributed objects in SAR imagery.