The accurate knowledge of the geometry of an airborne SAR image is crucial for many applications: Repeat-pass SAR interferometry requires an accurate image matching to the 10(th) of a pixel, while less demanding applications such as wide area coverage by multi-pass composite or image geocoding tolerate mismatches of pixels. Compared to spaceborne SAR, those accuracy requirements are stronger for airborne SAR since they provide higher resolution. Moreover, irregularities in aircraft motion due to air turbulence introduce severe geometrical distortions in the images. Unfortunately, these distortions are tightly coupled with the signal processing algorithm used for computing SAR images. We have implemented a geometrical error model for our generic off-line SAR processor which provides an image distortion map. Derivatives with respect to errors in radar parameters and errors in aircraft trajectory measurements (velocity, altitude, oscillations) are also provided, thus allowing the efficient estimation of the errors from distortion measurements (tiepoints). The paper is illustrated with some relevant application examples.
