Geocoding Based on Recovery of Image Acquisition 
Parameters 
In this approach, ground control points described by 
three-dimensional object coordinates are transformed into 
the image space. Differences detected by location checks 
using the homologue image points are taken as parameters for 
a preliminary adjustment of imaging characteristics, in 
particular of sweep delay, time off-set and scale factors, 
Then, in analogy to the photogrammetric approach, 
measurements of image coordinates of control points and the 
SAR projection relations can be combined and optimized in gj 
complex bundle adjustment procedure leading to a restitution 
of ephemeris data. Thus, the underlying radargrammetric 
model for the final image-to-object space transformation is 
adequately adapted to provide a valid description of the 
original image geometry. 
It is evident that, within limits, both geocoding 
methods are able to tolerate only approximately given 
ephemeris data. In different ways, they both recover 
consistency of the radargrammetrio model with the geometric 
distortions appearing in the input SAR image. However, a 
comparison of advantages and draw-backs of these two 
algorithms would go beyond the scope of this paper. 
Image-to-map rectification offers the possibility to 
integrate SAR image data into geographic information systems 
(cf. Howard 1985) and to efficiently convert mosaics of 
geocoded SAR images into radar image maps. Change detection 
for topographic and thematic map revision and the correction 
or concentration of information in geodata bases are other 
applications. Moreover, in many cases it is a prerequisite 
to the registration of multi-sensor remote sensing data. 
3. STEREOSCOPY 
In principle, radargrammetric fusion of two SAR images 
covering the same area but referable to different image data 
acquisition parameters enables the reconstruction of 
three-dimensional object coordinates. Two such images from 
a SAR image stereo-pair. However, the sensor position 
distance must not be too long (cf. Raggam et al. 1985). 
Terrain information of both images is transformed into 
the object space. In doing so, attention must be paid that 
each of them is transferred using the respective sensor 
model. The intersection points of any two range projection 
circles passing through identical points in the two images 
are determined, usually in a least Squares adjustment 
calculation. The coordinates of these intersection points 
represent location and elevation of the imaged object 
points. 
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