Radar is a crucial tool for detecting subsurface structures and properties on Mars. The shallow radar (SHARAD) aboard the Mars reconnaissance orbiter (MRO) has conducted almost comprehensive orbital surveys of Mars over the past two decades, which provides a lot of valuable data for detection of Mars. However, the current research on the inversion and interpretation of SHARAD data mainly focuses on the part containing subsurface reflection, and the surface reflection data, which accounts for the largest proportion, has not been fully utilized. In 2021, the US“Perseverance”rover and China’s“Zhurong”rover successfully landed in Jezero Crater and southern Utopia Planitia, respectively. Both rovers were equipped with ground-penetrating radar systems and collected a large amount of data, providing crucial references for calibrating SHARAD surface reflection data. Firstly, the SHARAD data is processed to eliminate the influence of ionosphere interference, satellite attitude and ground roughness. Then, the low-frequency channel radar data from Mars rover penetrating radar (RoPeR) on“Zhurong”rover are processed and inverted to calibrate the surface reflection power of SHARAD data. Finally, a permittivity distribution map of the southern Utopia Planitia is generated based on the processed SHARAD surface reflection power. The results indicate that the permittivity map in southern Utopia Planitia is relatively uniform, ranging from 3.5 to 4.5, but the permittivity values in the southern highland are slightly higher than those in the northern lowland. A data processing and inversion method by combining SHARAD and RoPeR is proposed in this study, which can help improve the large-scale data processing and interpretation capabilities of Mars radar and enhance the understanding of Mars surface properties and evolution history.

As the modern electromagnetic environment becomes more complex, the demand for spatial multi-beamforming is growing. The digital array radar (DAR) exhibits advantages such as flexible waveform design and controllable multi-beam generation. However, in the complex battlefield environments, how to achieve deep null suppression against strong interferences, or implement null suppression in a certain width of the angle range while maintaining transmitting power is a challenging problem. In this paper, based on the digital array radar, the research work of its diverse multi-beamforming method is carried out. By constraining the weighted amplitude, the fluctuation characteristics of the weighted amplitude on each antenna are reduced, and higher transmission efficiency is obtained while maintaining performance.

In response to the characteristics of high mobility of combat platforms, mechanical motion, complex terrain, and dynamic external environments, achieving high-precision antenna pointing is crucial for vehicle-mounted phased array radars to ensure accurate target positioning. Focusing on the antenna of vehicle-mounted phased array radars, this study investigates the sources of mechanical pointing errors and establishes error models for evaluation and sensitivity analysis. Combined with the engineering feasibility, the precision decomposition of each device is carried out, sensors are deployed to monitor deviations, while design-based precision compensation and safeguards are implemented from the design point of view. Precision testing is conducted for individual components and the integrated system under segmented conditions. Combined with the instrument accuracy and test data, antenna mechanical pointing errors are compensated. Validation is performed through two types of far-field experiments. Data comparison demonstrates that the proposed analysis and testing methodology enhances the accuracy and reliability of antenna mechanical pointing in vehicle-mounted phased array radars, offering valuable insights for engineering applications.