IEEE Geoscience and Remote Sensing Magazine - March 2022 - 5

Continuing with the theme of algorithms, but moving
down in frequency to the microwave window, we come
to a tutorial on synthetic aperture radar (SAR) imaging by
Sun et al. SAR is now widely used in remote sensing applications
ranging from defense to geological mapping. Although
fundamental principles of SAR are well established,
it remains a very active area for research, moving from lowEarth
orbit (LEO) to middle-Earth orbit (MEO) and geostationary
(GEO), with submeter resolution. Advancements in
algorithms for new imaging modes have driven progress in
this field.
This article aims to provide a generalization and
summary of the state of the art in SAR imaging. Starting
with fundamental principles, the article reviews their
implementation in imaging algorithms for single-channel
LEO-SAR, multichannel LEO-SAR, and MEO/GEOSAR.
Stripmap, spotlight, and sliding spotlight modes
are described with a unified focusing algorithm for all
modes. Looking to the future, ultrahigh resolution and
wide coverage are important research directions, as is the
evolution to MEO/GEO platforms. These advances present
challenges that should motivate more research in SAR
imaging algorithms.
Next, the feature by Chen et al. reviews autofocus in airborne
SAR. Airborne platforms are preferred over satellites
in certain applications, such as precision agriculture or
environmental monitoring. In comparison to satellite orbits,
aircraft flight trajectories have much larger variability,
mainly due to atmospheric turbulence. This introduces
significant motion errors in the radar data, necessitating
the development of motion compensation (MoCo) or autofocus
techniques. A comprehensive review of high- and
ultrahigh-resolution, wide-beam, and squint MoCo/autofocus
methods is provided. Some of the research areas
discussed in the article include the estimation of motion
and azimuthal errors, particularly in light of the increasing
beamwidth and limitations of the traditional centralbeam
approximation.
The authors suggest that a more general autofocus
framework, encompassing all of the various imaging and
motion error estimation algorithms, is needed. Computational
resources remain a challenge with the increasing
volume of radar echo data being collected. Some suggested
areas for future research include combining MoCo methods
with time domain imaging, DL, and sparse imaging
mechanisms; autofocus for wide-beam systems; and realtime
MoCo/autofocus.
Keeping with the SAR theme but moving on to applications,
Ma et al. review the use of multitemporal interferometric
SAR (MTInSAR) for monitoring of the health of urban
infrastructure. It is now possible to use this technique
to detect deformations with accuracies of 2 mm per year.
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MARCH 2022 IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
5
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IEEE Geoscience and Remote Sensing Magazine - March 2022

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