For both of these constraints to be met simultaneously, we 
must have 
W = EAR therefore W zc 
D 
4Lv 2v 23 Ce) 
Thus, the achievable azimuth resolution is proportional to 
the swath width. Narrow swaths are necessary to achieve fine 
resolution. 
As a consequence of the side-looking configuration, SAR images 
have an unusual geometry. Look at figure 6, which shows a cross 
section at constant azimuth (along track position). Since cross track 
position is determined by a range measurement, the SAR effectively 
projects points on the terrain onto a line parallel to the line of 
sight from the radar. (We must be more careful if a large cross track 
swath is imaged due to changes in incident angle across the swath.) We 
first notice that, due to shadowing, at certain ranges not returned 
signal will be present. We next notice that small hills will be 
foreshortened, that is, their peaks will be displaced towards smaller 
ranges than will their bases. In an image, they will seem to be bent 
towards the radar. For large mountains, the situation can be so 
extreme that their peaks can be imaged completely to one side of their 
bases. The mountains appear to be lying on their sides; this effect is 
called layover. 
In addition to being distorted in this manner, SAR images are 
subject to a characteristic type of noise. This results from the 
coherent nature of the imaging process. The signal at any point on the 
image is the vector sum of the phasors representing the radar returns 
from all sources of scattering within the resolution of the radar. 
This is shown in figure 7. By the central limit theorem, the resultant 
phasors will be random normal distributions for the real and imaginary 
components. As a result, we can show that the power of the return (the 
squared magnitude) will have an exponential distribution 
pos nye tb (7) 
An exponentially distributed variate has a standard deviation equal to 
its mean. This is indeed a noisy type of noise. This type of multi- 
plicative noise is called speckle, because of its visual appearance on 
SAR images. It can be quite troublesome. One way of dealing with it 
is shown in figure 8, Instead of using the entire available SAR data 
span to produce one image, the SAR data are divided into sub-spans each 
of which is used to create a different statistically independent 
image. These images are averaged to quiet the noise. Because 
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