Active panels are generally applied in large aperture and high-frequency reflector antennas, and the precise calculation of the actuator adjustment value is of great importance. First, the approximation relationship between the adjustment value and panel elastic deformation is established. Subsequently, a panel adjustment matrix for the whole reflector is derived to calculate the reflector deformation caused by the actuator adjustment. Next, the root mean square (rms) error of the deformed reflector is expressed as a quadratic form in the matrix form, and the adjustment value can be derived easily and promptly from the corresponding extreme value. The solution is expected to be unique and optimal since the aforementioned quadratic form is a convex function. Finally, a 35 m reflector antenna is adopted to perform the panel adjustments, and the effect of the adjustment errors is discussed. The results show that compared with the traditional model, where the panel elastic deformation is not considered, the proposed method exhibits a higher accuracy and is more suitable for use in large reflectors with a high operation frequency. The adjustment errors in different rings exert different influences on the gain and sidelobe level, which can help determine the actuator distribution with different precisions.

The NanShan Radio Telescope is a 26-m fully steerable radio telescope, and it adopts a 6-UPU Stewart platform with electric motors to adjust and align the position of the subreflector. In order to analyze the actual dynamic performance and control the Stewart platform of the NanShan Radio Telescope, this article models the inverse dynamic of the Stewart platform using the virtual work approach. The model improves the accuracy of the dynamic equations and considered the pitching motion of the base platform in the practical application of the radio telescope. Dynamic simulations of the Stewart platform are implemented, the conditions of the passive rotation of the piston of actuators are considered, and the results show that the effect of the passive rotation of the pistons of the actuators is important to obtain more accurate result. The conditions of the system under the different elevation angles of the radio telescope are also considered, and the results show that the change of the elevation angles of the radio telescope has a great impact on the driving forces of the Stewart platform. It is known from the analysis that the passive rotation of pistons of actuators and the elevation movement of the primary reflector of the radio telescope are not ignorable for the precise analysis and control of the Stewart platform of the NanShan Radio Telescope.

Tree roots are vital for tree ecosystems; accurate root detection helps analyze the health of trees and supports the effective management of resources such as fertilizers, water and pesticides. In this paper, a deep learning-based ground-penetrating radar (GPR) inversion method is proposed to simultaneously image the spatial distribution of permittivity for subsurface tree roots and layered heterogeneous soils in real time. Additionally, a GPR simulation data set and a measured data set are built in this study, which were used to train inversion models and validate the effectiveness of GPR inversion methods.The introduced GPR inversion model is a pyramid convolutional network with vision transformer and edge inversion auxiliary task (PyViTENet), which combines pyramidal convolution and vision transformer to improve the diversity and accuracy of data feature extraction. Furthermore, by adding the task of edge inversion of the permittivity distribution of underground materials, the model focuses more on the details of heterogeneous structures. The experimental results show that, for the case of buried scatterers in layered heterogeneous soil, the PyViTENet performs better than other deep learning methods on the simulation data set. It can more accurately invert the permittivity of scatterers and the soil stratification. The most notable advantage of PyViTENet is that it can accurately capture the heterogeneous structural details of the soil within the layer since the soil around the tree roots in the real scene is layered soil and each layer of soil is also heterogeneous due to factors such as humidity, proportion of different soil particles, etc.In order to further verify the effectiveness of the proposed inversion method, this study applied the PyViTENet to GPR measured data through transfer learning for reconstructing the permittivity, shape, and position information of scatterers in the actual scene. The proposed model shows good generalization ability and accuracy, and provides a basis for non-destructive detection of underground scatterers and their surrounding medium.

In this paper, a method based on the Zernike distribution and the optical aberration is proposed to investigate the effects of the distribution characteristics of surface distortions of a reflector antenna on its electromagnetic performance (EMP). For large-scale errors, an analytical model is introduced to describe the arbitrary distortions, based on the orthogonal Zernike polynomials. The effects of error distribution described by the Zernike series on typical EMP are analyzed. The numerical results indicate that the distortions in the distribution feature of defocus or spherical aberration have a greater impact on gain, and the distribution feature of tilt or coma mainly influences boresight offset; the distribution feature of defocus, astigmatism, and spherical aberration has a greater impact on sidelobe levels. The results indicate that the beam contour patterns are related to the distribution forms of distortions and are similar with the same aberration feature. On the basis of the Seidel aberration, the relationships between typical EMP and the aberration coefficient are presented. Based on these, the error profile of the primary influence and the approximate feature of EMP can be determined, and the antenna performance can be predicted in a simple manner.

Large reflector antennas are widely used in radars, satellite communication, radio astronomy, and so on. The rapid developments in these fields have created demands for development of better performance and higher surface accuracy. However, low accuracy and low efficiency are the common disadvantages for traditional panel alignment and adjustment. In order to improve the surface accuracy of large reflector antenna, a new method is presented to determinate panel adjustment values from far field pattern. Based on the method of Physical Optics (PO), the effect of panel facet displacement on radiation field value is derived. Then the linear system is constructed between panel adjustment vector and far field pattern. Using the method of Singular Value Decomposition (SVD), the adjustment value for all panel adjustors are obtained by solving the linear equations. An experiment is conducted on a 3.7 m reflector antenna with 12 segmented panels. The results of simulation and test are similar, which shows that the presented method is feasible. Moreover, the discussion about validation shows that the method can be used for many cases of reflector shape. The proposed research provides the instruction to adjust surface panels efficiently and accurately.

The efficiency of a reflector antenna highly depends on its surface shape. In order to ensure a good convergence, the conventional phase retrieval based shape detection schemes require that several far-field intensities be scanned, focused, or defocused. For large reflector antennas, the scanning process is time consuming. This paper proposes a new shape detection method that requires only single far-field intensity. Unlike existing shape detection methods, it retrieves both the amplitude and the phase, based on the fact that a deformed shape causes change not only in the aperture phase but also in the aperture amplitude. Through even-odd decomposition analysis, it is found that in the case of small and smooth deformation, “odd-phase” and “even-amplitude” can be directly recovered from one focused far-field intensity. This leads to the recovery of both the odd and the even parts of the antenna surface shape simultaneously. By combining amplitude retrieval and phase retrieval, this work achieves for the first time the shape detection with only one scan.