IEEE Geoscience and Remote Sensing Magazine - March 2022 - 179

two SVDs. The first is to correct the azimuth variant of the
first characteristic component, and the second to correct
the azimuth variant of the second characteristic component.
The two SVDs are connected by the azimuth nonlinear
scaling function. After the azimuth space-variant correction,
the azimuth compression can be used to obtain
accurate imaging results.
Aiming at the serious azimuth space-variant problem
in the MEO/GEO-SAR, a new azimuth space-variant correction
method based on the JTDR is proposed [132]. The
method can simultaneously process the azimuth linear and
quadratic space variance shown in Figure 20. An algorithm
flowchart is shown in Figure 21.
The azimuth time domain resampling is first used to
remove the azimuth space-variant characteristics of the
Doppler modulation frequency. Then, the RCMC can be
achieved by the CSA. For the problem of the azimuth precise
focusing being affected by the residual space variance
of the Doppler parameters, a second azimuth resampling
is performed in the Doppler domain. The high-order Doppler
and coupled space variances of the range and azimuth
Raw Data
Azimuth Resampling
Time Resampling
σ1, σ2
Modified CSA
Azimuth FFT
Hrcs
Range FFT
Hrc, Hrcmc
Range IFFT
Hmat, Hres
Doppler Resampling
Azimuth Resampling
Azimuth FFT
Geometry Correction
Focused Image
FIGURE 21. A flowchart of the joint time-Doppler resampling algorithm. rcs: scaling function; mat: azimuth-invariant phase compensation
function; res: residual video phase compensation function.
MARCH 2022 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
179
g21, g31
Fitting Parameters
of the Range History
Processing Parameters
GPS Data
Scene
Parameters
can be uniformly corrected
by the azimuth Doppler domain
resampling, thereby
eliminat ing the azimuth
space variance of the phase
modulation of the different
targets in the large scene and
realizing the unified focusing
of the large scene.
CONCLUSION
Spaceborne SAR plays a vital
role in remote sensing. Since
the first decade of 21st century,
spaceborne SAR approaches
have rapidly developed, and they have made a technological
leap forward in recent years. Imaging algorithms
directly determine the image quality of spaceborne SAR,
and they are the basis of and key to this research field. Thus,
generalizing and summarizing the imaging algorithms for
spaceborne SAR are of great significance.
MEO/GEO-SAR HAS GOOD
APPLICATION PROSPECTS IN
TOPOGRAPHIC MAPPING,
NATURAL DISASTER
MONITORING, AND
FORECASTING. HOWEVER,
THE RISE OF THE ORBIT
INEVITABLY BRINGS NEW
PROBLEMS.

IEEE Geoscience and Remote Sensing Magazine - March 2022

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