| Summary: | This thesis investigates the reasons for, and proposes correction methods to reduce the
scalloping inherent in the range dimension in images processed using the SPECAN SAR
processing algorithm. These corrections methods are successfully tested using ERS-1 satellite
data.
The SPECAN algorithm was developed in 1979 by MacDonald Dettwiler and Associates, as
a multilook version of the deramp/FFT method of pulse compression. The algorithm provides
an efficient method of producing spaceborne SAR imagery of modest resolution, which makes it
ideal for quicklook imaging. Widespread use of the algorithm in quicklook imaging, however,
is hindered by the scalloping present in both the range and azimuth dimensions of the image.
This thesis concentrates on correction of range scalloping by presenting explanations for the
two types of scalloping present in the range dimension of SPECAN processed images. The basic
scalloping present in all scenes is due to the time variation in the envelope of the transmitted
signal. The extra scalloping seen in some scenes is due to clipping of the ERS-1 raw data.
Because of the geometry of the SPECAN processing cycles, the radiometry of the output is
sensitive to the transmitted chirp amplitude. The 0.5 dB power difference between the beginning
and end of the transmitted chirp is reflected in each compressed output segment, creating a
periodic lightening and darkening throughout the image. This banding effect is especially
noticeable in low contrast scenes. This problem is corrected using the chirp replica which
is embedded in the data header as an estimate of the pulse shape.
The extra scalloping observed in some high reflectivity scenes is attributed to the clipping
of the ERS-1 raw data in these scenes. Clipping causes attenuation in the output power. This
power loss varies along range according to the degree of saturation, and is different for each
compressed data block, thereby creating a discontinuity between adjacent compressed segments
which adds to (or subtracts from) the basic scalloping effect. This problem is corrected using the
relationship between power loss and degree of saturation in the Gaussian distributed raw data. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate
|
|---|
