A Modified Iteration-Free SPGA Based on Removing the Linear Phase

In traditional Stripmap SAR imaging, the platform motion error will bring the phase error in the azimuthal direction to the image, which will have a series of effects on the imaging quality. The traditional autofocus algorithm—Stripmap Phase Gradient Algorithm (SPGA)—can estimate any order phase error above the second order in theory, but it is difficult to estimate the linear phase error, which leads to the discontinuity of the estimated phase error. It usually needs multiple iterations to focus an image, which is inefficient. Moreover, because the linear phase error cannot be estimated, the traditional SPGA cannot eliminate the target offset in the image, resulting in the distortion of the image in the azimuthal direction. According to the continuity of phase error, we propose a modified iteration-free SPGA based on removing the linear phase. Without iteration, the proposed autofocus algorithm can achieve comparable or even better results than traditional SPGA. In the simulation experiments, piecewise linear errors are added to the images of multiple targets. SPGA still fails to focus the image after six iterations. The average ILSR and ILSR are −7.11 dB and −3.99 dB, respectively, and the average number of point target drift is 8.42 pixels. The proposed algorithm optimizes the average ILSR and ILSR to −12.34 dB and −9.87 dB and reduces the average number of point target drift to 0.16 pixels. In the actual data processing, using image entropy as the evaluation criterion, the time consumption is only 19.25% of SPGA under the condition of achieving the same focusing quality

A Channel-Adaptive Range-Doppler Domain Filtering Serial BAQ Algorithm and Comparative Analysis

With the growing demand for large-scale urban observation, multi-channel technology has become a cornerstone of high-resolution wide-swath SAR systems. The challenge of storing and transmitting the large data volumes generated by multi-channel systems has driven the development of advanced data compression techniques. However, in onboard implementations with non-power-of-two channel numbers and serial data formats, the existing multi-channel compression algorithms reveal significant conflicts involving channel counts, FFT cores, and the Krieger method. To address these issues, this paper introduces the Channel-Adaptive Range-Doppler domain filtering Serial Block Adaptive Quantization algorithm (CARDS-BAQ). By incorporating a point-frequency RD domain filtering approach and leveraging serial data matrix splicing and rollback combined with point-frequency ABAQ, CARDS-BAQ enables efficient data compression for arbitrary channel counts. The performance of CARDS-BAQ is validated using GF-3 measured data through comparative analysis with BAQ, ABAQ, MCBAQ, and 3MBAQ algorithms under power-of-two channel conditions. Additionally, its applicability and reliability for non-power-of-two channel numbers are demonstrated through payload flight experiments conducted in 2024 in Yingkou, Liaoning Province, China. CARDS-BAQ effectively supports data storage and transmission for large-scale urban observation, marking a significant advancement in remote sensing technology

Position and Orientation System Error Analysis and Motion Compensation Method Based on Acceleration Information for Circular Synthetic Aperture Radar

Circular synthetic aperture radar (CSAR) possesses the capability of multi-angle observation, breaking through the geometric observation constraints of traditional strip SAR and holding the potential for three-dimensional imaging. Its sub-wavelength level of planar resolution, resulting from a long synthetic aperture, makes CSAR highly valuable in the field of high-precision mapping. However, the motion geometry of CSAR is more intricate compared to traditional strip SAR, demanding high precision from navigation systems. The accumulation of errors over the long synthetic aperture time cannot be overlooked. CSAR exhibits significant coupling between the range and azimuth directions, making traditional motion compensation methods based on linear SAR unsuitable for direct application in CSAR. The dynamic nature of flight, with its continuous changes in attitude, introduces a significant deformation error between the non-rigidly connected Inertial Measurement Unit (IMU) and the Global Positioning System (GPS). This deformation error makes it difficult to accurately obtain radar position information, resulting in imaging defocus. The research in this article uncovers a correlation between the deformation error and radial acceleration. Leveraging this insight, we propose utilizing radial acceleration to estimate residual motion errors. This paper delves into the analysis of Position and Orientation System (POS) errors, presenting a novel high-resolution CSAR motion compensation method based on airborne platform acceleration information. Once the system deformation parameters are calibrated using point targets, the deformation error can be directly calculated and compensated based on the acceleration information, ultimately resulting in the generation of a high-resolution image. In this paper, the effectiveness of the method is verified with airborne flight test data. This method can compensate for the deformation error and effectively improve the peak sidelobe ratio and integral sidelobe ratio of the target, thus improving image quality. The introduction of acceleration information provides new means and methods for high-resolution CSAR imaging

Gold-Catalyzed Hydration of Haloalkynes to α‑Halomethyl Ketones

A general atom-economical approach for the synthesis of α-halomethyl ketones is demonstrated through hydration of a wide range of haloalkynes. Other outstanding features include excellent yields from both alkyl- and aryl-substituted haloalkynes and wide functional group tolerance. This protocol is an alternative to conventional α-halogenation of ketones