The complex and diverse geological structures on the lunar surface serve as a direct record of its long evolutionary history. Comprehensively identifying and classifying these geological structures can not only deepen our understanding of lunar evolution, but also support the planning of future lunar exploration missions and guide the detection of lunar energy resources. However, the diverse and intricate morphologies of lunar geological structures, coupled with certain similarities between different formations, make their automatic identification and classification a significant challenge. To address this issue, we propose a multi-type lunar geological structure recognition network based on cross-view constraints, which mines differentiated feature information to enhance target identification and discrimination capabilities. This network effectively extracts heterogeneous and complementary features through cross-view feature extraction constraints. By employing a discrepancy-weighted loss function, the network focuses on regions where discrepancies arise in the recognition results across multiple views, thereby enhancing attention to divergent areas and learning feature representations in complex scenarios. Additionally, multi-scale contextual information aggregation combines contextual features from different receptive fields, leveraging surrounding terrain to enhance discriminative information for lunar geological structures. Experimental results demonstrate that the proposed method exhibits significant superiority in the task of identifying and classifying multi-type lunar geological structures, with a 1.9% improvement in mIoU.

The infinity and orthogonality of the orbital angular momentum (OAM) of vortex electromagnetic waves (VEMWs) provide a new degree of freedom for the modulation of information. The VEMW generated by the uniform circular array (UCA) exhibits the characteristics of the Bessel function in terms of amplitude, and there is a null amplitude region in the beam center. This characteristic is particularly obvious when the array radius is small. In practical applications, it is usually necessary to switch OAM mode to ensure the richness of the received information. This leads to a sudden drop in radiation energy when switching OAM modes, and the OAM mode cannot be fully utilized. To address this issue, this paper proposes an OAM mode switching method based on the characteristics of the intersection of the adjacent-order Bessel functions for radar forward-looking imaging. Meanwhile, this paper introduces OAM mode repetition frequency (OMRF) to indicate the “speed” of switching OAM mode. Finally, through the application in the field of forward-looking radar imaging, it is proved that the method proposed in this paper can effectively improve the OAM mode utilization rate and anti-noise ability.

Topography exerts a significant influence on the polarimetric parameters of synthetic aperture radar (SAR), making its study crucial for advancing scientific research. Accurate analysis of topography-independent content requires the removal of lunar topography effects. This letter presents a statistical-based method for assessing the impact of topography on SAR images. It involves the calculation of various SAR parameters and local incidence angle (LIA) using Lunar Reconnaissance Orbiter’s (LRO) Mini-RF SAR and Lunar Orbiter Laser Altimeter (LOLA) digital elevation model (DEM) data, respectively. By establishing a mapping relationship between LIA and SAR parameters through coregistration, the proposed method enables an insightful examination of topography effects. The method is applied to analyze and mitigate topography influences on lunar SAR images acquired by Mini-RF, indicating that LIA has a pronounced effect on SAR parameters in relatively flat areas, while its correlation weakens in rougher regions. This analysis provides valuable insights for classifying lunar regolith based on the effects of topography on SAR images.

Lunar crater ejecta can provide important information regarding the impact cratering process and the properties of subsurface materials. However, the mapping of the range of the crater ejecta has been hampered by the degradation of the lunar surface’s morphological features. Polarimetric synthetic aperture radar (SAR) is an effective technique to determine the scattering characteristics of the lunar surface and subsurface, and for distinguishing the fresh crater ejecta from surrounding regions. This letter uses a three-component compact decomposition to process the Mini-RF data to identify the scattering characteristics of the crater floor, crater wall, crater ejecta of the simple fresh crater, and lunar background regolith. Then, a method for mapping the range of crater ejecta is proposed to obtain the boundary between the crater ejecta and other regions by analyzing the differences in polarimetric scattering characteristics. Using this method, the crater ejecta of six craters were extracted and verified with the range of the ejecta obtained through visual interpretation on SAR imagery, the accuracy of the ejecta range obtained by the proposed method is 82%-95%. The results show that the proposed method can effectively depict the range of the simple fresh lunar crater ejecta.

Synthetic Aperture Radar (SAR) images of Sentinel-1 (S-1) in Interferometric Wide (IW) swath mode, which are widely used for land and ocean services, but are affected by severe radio frequency interference (RFI). Single Look Complex (SLC) data containing phase and amplitude information is the most popular product type for SAR applications. The sub-band spectral cancellation (SSC) method extracts and suppresses RFI in SLC images through making a subtraction among different sub-images, which is efficient and strong enough to be applied to projects based on the hypothesis that the range spectrum is particularly symmetric. However, through the theoretical analysis of the imaging algorithm for generating SLC data in S-1 IW mode, it is found that the phase compensation step in the azimuth post-processing destroys the symmetry of the spectrum and does not meet the basis for the application of the SSC method, resulting in poor RFI mitigation performance. Based on this discovery, inverse phase compensation is first performed on the RFI-contaminated SLC image to restore the spectrum symmetry. The second step is the sub-band division and sub-image energy cancellation. This method effectively protects useful signals while suppressing RFI, which is significantly essential for the further application of S-1 SLC images. The availability of the method has been proved by simulated and measured experiments.

Although the multiple-phase-sectionalized-modulation (MPSM) jamming can produce barrage jamming effects in a local range, the range of barrage jamming can't be controlled. Against this disadvantage, an improved MPSM jamming method based on a non-linear frequency-modulate (NLFM) signal, i.e., MBN, is proposed in this paper. The MBN realizes the control of the jamming range in the fast time domain based on the controllable time-frequency structure of the NLFM signal. To generate the desired NLFM signal, the shaping factor is defined. Subsequently, the feasibility and effectiveness of the MBN jamming method are confirmed by simulation experiments.

The concept of spaceborne interrupted frequency-modulated continuous-wave (IFMCW) synthetic aperture radar (SAR) subverts the design principles of the traditional frequency-modulated continuous-wave (FMCW) SAR system, which uses a single physical antenna to transmit signal and receive echo alternatively. Due to the demand of turning off the receiver in the process of transmitting signal, periodical data-missing phenomena will be aroused in the echo data, and the missing ratio is close to 50%. When traditional imaging algorithms were used to process the echo data, the artifacts, appearing as periodically replicated false targets, will be generated in the focused SAR image due to the periodical missing data, thus affecting the image interpretation. In order to effectively suppress the artifacts, a novel method exploiting singular value threshold-based matrix completion (SVT-MC) technology was proposed in this letter, where the singular value decomposition of the Hankel matrix was utilized to recover the missing data with high precision. Finally, the experimental results based on both point targets and distributed targets verify the effectiveness and superiority of the proposed method.

Synthetic aperture radar (SAR) is an advanced ground-observing remote sensing technology, and high-resolution wide-swath (HRWS) imaging has always been the goal of SAR. In general, an improved azimuth resolution requires a large pulse repetition frequency (PRF), resulting in high system requirements. To overcome this difficulty, azimuth multichannel technology has gradually developed, achieving HRWS imaging and decreasing the PRF by increasing the spatial sampling, i.e., increasing the number of antenna subapertures in the azimuth. This article proposes a theoretical architecture that generates multiple virtual receiving apertures in the azimuth rather than real apertures. The virtual receiving apertures are formed by multiplying the azimuth signals by linear phase histories provided by vortex beams carrying different orbital angular momentum (OAM) modes. Vortex beams with different OAM modes have different oblique phase wavefronts, so virtual receiving positions are generated in the along-track direction. This approach aims to reduce the PRF without increasing the azimuth real receiving aperture. Simulation results demonstrate the effectiveness and limitations of the method. Finally, to overcome the inherent limitations of the method, two possible implementation schemes are proposed.