High Phase-Preserving Autofocus Imaging for Squinted Airborne Synthetic Aperture Radar | IEEE Journals & Magazine | IEEE Xplore

Figure 1.

This figure illustrates the geometry of a squinted airborne SAR (Synthetic Aperture Radar) system and shows why motion errors are problematic.

Key elements explained simply:

The Aircraft and Radar:

• The aircraft is flying along a path with velocity v
• θ₀ is the squint angle - how much the radar beam is angled relative to perpendicular
• The radar is looking sideways and slightly forward/backward, not straight down

Two Flight Paths:

• Blue line (Ideal trajectory): Where the aircraft should fly in perfect conditions
• Black curved line (Real trajectory): Where the aircraft actually flies due to atmospheric turbulence, wind, etc.

The Problem:

• The difference between these paths is ΔR (motion error)
• Point P on the ground is being imaged
• R₀ is the ideal distance to the target
• R is the actual distance due to the aircraft being off course

Why This Matters: In traditional broadside SAR (looking straight to the side), small motion errors are easier to correct. But in squinted SAR:

• The angled viewing geometry makes the system much more sensitive to these motion errors
• Different parts of the image are affected differently by the same motion error
• This creates spatially variant distortions that are computationally expensive to correct

The researchers' breakthrough was developing an efficient algorithm to handle both the geometric effects of the squint angle and the motion errors simultaneously, rather than treating them as separate problems.

Radar Algorithm Breakthrough Tackles Squinted SAR's Computational Challenge

New processing technique dramatically reduces costs while preserving image quality for angled radar systems

Squinted synthetic aperture radar (SAR) has long offered tantalizing advantages over traditional broadside imaging—longer target illumination times, improved cross-range resolution, and enhanced moving target detection. But these benefits have come at a steep computational price that has limited widespread adoption. Now, researchers at Central South University in China have developed an algorithm that could change that calculus entirely.

Published in the January 2025 issue of IEEE Transactions on Geoscience and Remote Sensing, the work addresses a fundamental challenge that has plagued squinted SAR since its early implementations in systems like the Lynx GMTI/SAR radar: how to efficiently process the complex, spatially variant signals that result from angled radar viewing geometries.

The Squint Advantage and Its Costs

Traditional SAR systems image areas perpendicular to the aircraft's flight path, creating strip maps as the platform moves forward. Squinted operation, by contrast, angles the radar beam forward or backward relative to the platform's velocity vector—typically between 45 and 135 degrees due to geometric constraints.

This angular viewing provides significant operational advantages. Extended illumination times create larger synthetic apertures, improving cross-range resolution. The longer dwell times are particularly valuable for ground moving target indication (GMTI), where distinguishing moving objects from stationary clutter requires extended observation periods.

But squinted geometries break many of the mathematical simplifications that make broadside SAR processing tractable. The angular viewing creates range-dependent Doppler variations, severe range cell migration that varies across the scene, and spatially variant phase errors that resist conventional correction techniques.

"The computational expense has been the limiting factor," explains Dr. Jianlai Chen, lead author of the new study. "Different parts of the scene have different motion characteristics relative to the radar, and traditional algorithms handle each problem separately, multiplying the processing burden."

Coupled Problems, Unified Solution

Previous approaches treated the two main error sources independently: geometric distortions from the squinted viewing angle and motion errors from atmospheric turbulence affecting the aircraft. This separation ignored a crucial insight—the two phenomena are fundamentally coupled.

The researchers' breakthrough came from recognizing that Linear Range Walk Correction (LRWC)—a preprocessing step used to reduce range-azimuth coupling in squinted geometries—doesn't operate in isolation from motion compensation. The LRWC process can either exacerbate or mitigate platform motion errors, depending on the specific squint geometry and error characteristics.

Chen's team developed what they call "modified azimuth resampling," which addresses both error sources simultaneously with a single correction factor. Think of it as computational image stabilization operating on raw radar signals before conversion to visual images.

"By handling geometric distortions and motion errors together, we achieve better results with significantly improved computational efficiency," notes co-author Dr. Hanwen Yu, an IEEE Fellow at the University of Electronic Science and Technology of China.

Phase Preservation: The Hidden Challenge

Beyond computational efficiency, the algorithm tackles another critical issue that has limited squinted SAR applications: phase preservation. While amplitude information creates the familiar grayscale radar images, phase information enables interferometric analysis—the technique that allows detection of ground movements as small as millimeters.

Phase preservation is notoriously fragile in squinted geometries. The complex correction algorithms traditionally used often degrade phase coherence, limiting the processed images' utility for advanced applications like earthquake monitoring, infrastructure health assessment, and glacier tracking.

The new algorithm maintains phase integrity across multiple observation passes, enabling time-series analysis of ground deformation. In validation tests using real airborne data, the researchers achieved coherence coefficients exceeding 0.7 across most imaged areas—performance that enables subsequent interferometric processing.

Real-World Validation

The team validated their algorithm using X-band airborne SAR data collected over urban areas in China with squint angles of approximately 20 degrees. Compared to three existing methods, their approach achieved the lowest image entropy values—a standard measure of focusing quality—across all test regions.

More significantly, interferometric processing of multi-pass data demonstrated clear interference fringes and high coherence, confirming that the algorithm preserves the delicate phase relationships needed for advanced applications.

The computational analysis reveals processing costs falling between traditional full-aperture methods and more expensive subaperture approaches. For typical scenarios, the new algorithm requires approximately 2.3 times the computation of basic full-aperture methods—a significant improvement over subaperture techniques that can require 3.7 times the baseline processing load.

Market Implications

The timing coincides with explosive growth in the SAR market. Industry analysts project the global synthetic aperture radar market will reach $7.33 billion by 2033, driven by increasing demand for Earth observation, disaster management, and environmental monitoring applications.

Commercial operators like Finland's ICEYE and California-based Capella Space are democratizing access to high-resolution radar imagery, offering 50-centimeter resolution images for thousands of dollars with delivery within hours. However, most commercial systems focus on simple imaging rather than the sophisticated interferometric applications that require phase preservation.

The computational efficiency gains could make squinted SAR more attractive for operational systems. "Phase-compatible preprocessing frameworks like this could enable multiplatform SAR cooperative imaging," Chen notes. "When operating multiple platforms, inconsistent data phases create fusion difficulties. This framework can unify phases and improve fusion quality."

Future Missions

The breakthrough comes as major space missions prepare to leverage advanced SAR capabilities. NASA and ISRO's joint NISAR mission, scheduled for launch in March 2025, will be the world's first dual-frequency SAR satellite, mapping the entire globe every 12 days with millimeter-level precision for deformation monitoring.

While NISAR operates in broadside mode, the enhanced processing techniques developed for squinted geometries often benefit conventional SAR as well. The algorithm's emphasis on phase preservation could prove particularly valuable as interferometric analysis becomes increasingly central to climate science and disaster monitoring.

The Bigger Picture

Beyond immediate applications, the research represents a broader trend toward sophisticated signal processing that balances computational efficiency with scientific rigor. As SAR data volumes explode—driven by proliferating satellite constellations and increasing temporal resolution—algorithms that preserve information integrity while managing computational costs become critical.

The work also demonstrates the value of recognizing coupled phenomena in complex systems. By treating geometric corrections and motion compensation as interconnected rather than independent problems, the researchers achieved superior results with improved efficiency—a principle applicable far beyond radar processing.

"For the first time, this article proves through theoretical derivation that LRWC processing can effectively avoid nonsystemic range cell migration in squinted mode," the researchers note. This theoretical contribution, validated with real data, provides a foundation for future algorithm development.

As Earth observation enters an era of continuous global monitoring, advances in SAR processing efficiency ensure that sophisticated analytical capabilities keep pace with incoming data volumes. In applications ranging from infrastructure monitoring to climate science, every improvement in our ability to process radar data cost-effectively brings us closer to the insights needed to address our planet's most pressing challenges.

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References

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This article is based on "High Phase-Preserving Autofocus Imaging for Squinted Airborne Synthetic Aperture Radar" by Jianlai Chen et al., published in IEEE Transactions on Geoscience and Remote Sensing, Vol. 63, 2025.

J. Chen et al., "High Phase-Preserving Autofocus Imaging for Squinted Airborne Synthetic Aperture Radar," in IEEE Transactions on Geoscience and Remote Sensing, vol. 63, pp. 1-15, 2025, Art no. 5215315, doi: 10.1109/TGRS.2025.3587539.

Abstract: For high-resolution squinted airborne synthetic aperture radar (SAR) imaging, both linear range walk correction (LRWC) and motion error introduce significant azimuth spatial-variant (ASV) characteristics in the radar echo, rendering the classical assumption of “azimuth translational invariance” no longer valid. Existing subaperture methods attempt to overcome the ASV characteristics of the signal by performing segmentation processing in the data domain or the image domain. However, grating lobes or image stitching problems inevitably occur in the focused images. Existing full-aperture methods, on the other hand, utilize azimuth resampling or nonlinear chirp scaling (NCS) to address the ASV problem. Nevertheless, the above-mentioned methods basically handle the ASV characteristics introduced by LRWC and motion errors separately, without considering the coupling characteristics between the two. Therefore, this article proposes a high phase-preservation squint airborne SAR autofocus imaging method by modifying the traditional azimuth resampling processing, so that only a single azimuth resampling factor is required to simultaneously solve the ASV problems brought about by LRWC and motion errors. The imaging processing results of airborne squint SAR real data verify its good focusing effect. Meanwhile, the interferometric processing results of multipass cross-track SAR real data also indicate that the proposed algorithm exhibits a high phase-preservation capacity. The images processed by the proposed algorithm and the comparison algorithms, as well as the multipass cross-track SAR complex images after registration, can be downloaded from https://pan.baidu.com/s/1okgAkp18ynK7qzKXe2lceQ?pwd=nquf
keywords: {Azimuth;Radar;Synthetic aperture radar;Radar imaging;Time-domain analysis;Trajectory;Couplings;Signal processing algorithms;Frequency-domain analysis;Focusing;Interferometric processing;linear range walk correction (LRWC);resampling;squinted autofocus;synthetic aperture radar (SAR)},

URL: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11075901&isnumber=10807682


High Phase-Preserving Autofocus Imaging for Squinted Airborne Synthetic Aperture Radar | IEEE Journals & Magazine | IEEE Xplore