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Owing to the platform instability and precision limitations of motion sensors, motion errors negatively affect the quality of synthetic aperture radar (SAR) images. The autofocus Back Projection (BP) algorithm based on the optimization of image sharpness compensates for motion errors through phase error estimation. This method can attain relatively good performance, while assuming the same phase error for all pixels, i.e., it ignores the spatial variance of motion errors. To overcome this drawback, a high-precision motion error compensation method is presented in this study. In the proposed method, the Antenna Phase Centers (APC) are estimated via optimization using the criterion of maximum image intensity. Then, the estimated APCs are applied for BP imaging. Because the APC estimation equals the range history estimation for each pixel, high-precision phase compensation for every pixel can be achieved. Point-target simulations and processing of experimental data validate the effectiveness of the proposed method.

Downward-looking Linear Array Synthetic Aperture Radar (LASAR) has many potential applications in the topographic mapping, disaster monitoring and reconnaissance applications, especially in the mountainous area. However, limited by the sizes of platforms, its resolution in the linear array direction is always far lower than those in the range and azimuth directions. This disadvantage leads to the blurring of Three-Dimensional (3D) images in the linear array direction, and restricts the application of LASAR. To date, the research on 3D SAR image enhancement has focused on the sparse recovery technique. In this case, the one-to-one mapping of Digital Elevation Model (DEM) brakes down. To overcome this, an optimal DEM reconstruction method for LASAR based on the variational model is discussed in an effort to optimize the DEM and the associated scattering coefficient map, and to minimize the Mean Square Error (MSE). Using simulation experiments, it is found that the variational model is more suitable for DEM enhancement applications to all kinds of terrains compared with the Orthogonal Matching Pursuit (OMP)and Least Absolute Shrinkage and Selection Operator (LASSO) methods.

Millimeter-wave Interferometric Synthetic Aperture Radar (InSAR) has smaller size, lower weight, and higher resolution compared with other bands. Thus, it has become a hot research topic. However, owing to its shorter wavelength, millimeter-wave InSAR data processing requires high-precision measurements of platform motion. For nonideal trajectories, traditional methods face difficulties in echo imaging and interferogram extraction. In addition, existing methods mainly produce SAR images based on plane projection. When the terrain changes abruptly, these methods may cause strong interferometric phase unwrapping and geometric distortion in SAR images. To overcome the abovementioned disadvantages of conventional methods in millimeter-wave InSAR imaging, an approach based on terrain surface projection is proposed. The echoes of different antennas are projected on the same terrain surface space for data imaging and interferogram extraction. In addition, the relation between terrain elevation and interferometric phase is derived. Simulations and experimental results verify the effectiveness of the proposed method; furthermore, the proposed approach improves the precision of interferometric phase extraction in complex motion conditions, while minimizing geometric distortion and phase wrapping in rough terrain, which is more conducive to terrain description and elevation inversion.

Compared with other bands, the millimeter wave Interferometric Synthetic Aperture Radar (InSAR) has high accuracy and small size, which is a hot topic in InSAR research. On the other hand, shorter wavelength causes difficulties in 2D imaging and interferometric phase extraction. In this study, the imaging and phase performance of the streaming Back Projection (BP) method combined with IMU data are analyzed and discussed on the basis of actual Ka-band InSAR data. It is found that because the wavelength of the Ka-band is short, it is more sensitive to the antenna phase-center history. To ensure the phase-preserving capacity, the IMU data must be used with accurate motion error compensation. Furthermore, during data processing, we verify the flat-earth-removing capacity of the BP algorithm that calculates and compensates the master and slave antenna phase centers individually.

Ferroptosis is a newly discovered type of cell death that exerts a crucial role in hepatic fibrosis. Formononetin (FMN), a natural isoflavone compound mainly isolated from Spatholobus suberectus Dunn, shows multiple biological activities, including antioxidant, anti‐inflammatory, and hepatoprotection. This research aims to explore the regulatory mechanism of FMN in liver fibrosis and the relationship between NADPH oxidase 4 (NOX4) and ferroptosis. The effects of FMN on HSC ferroptosis were evaluated in rat model of CCl4‐induced hepatic fibrosis. In vitro, N‐acetyl‐L‐cysteine (NAC) and deferoxamine (DFO) were used to block ferroptosis and then explored the anti‐fibrotic effect of FMN. The target protein of FMN was identified by bio‐orthogonal click chemistry reaction as well as drug affinity responsive target stability (DARTS), cellular thermal shift (CETSA), surface plasmon resonance (SPR) assays, and isothermal titration calorimetry (ITC) analysis. Here, we found that FMN exerted anti‐fibrotic effects via inducing ferroptosis in activated HSCs. NAC and DFO prevented FMN‐induced ferroptotic cell death and collagen reduction. Furthermore, FMN bound directly to NOX4 through possible active amino acid residues sites, and increased NOX4‐based NADPH oxidase activity to enhance levels of NADP+/NADPH, thus promoting ferroptosis of activated HSCs and relieving liver fibrosis. These results demonstrate that the direct target and mechanism by which FMN improves liver fibrosis, suggesting that FMN may be a natural candidate for further development of liver fibrosis therapy. [ABSTRACT FROM AUTHOR]