The radar cross-section (RCS) of power lines has an important significance for detection of the power lines. The method of moments (MoM) can calculate the RCS of power lines. However, the efficiency of the MoM is limited by the time-consuming computing process, as well as the expensive storage overhead. In order to enhance the efficiency and reduce the storage of the RCS calculation of power lines, we propose an RCS calculation method that combines the characteristic mode (CM) with a Sherman–Morrison–Woodbury formula-based algorithm (SMWA), which is referred to as a CM-SMWA. CMs are used as the basis functions for reducing the dimension of the MoM impedance matrix, and the SMWA is applied to directly solve the CMs-reduced matrix equation, which can reduce the computational time and storage. The numerical results demonstrate that the proposed method can obtain the RCS of power lines, with different incident angles and different polarizations, at a higher efficiency. At 35 GHz, compared with the conventional MoM, for a typical LGJ50-8 power line with a length of 0.276 m, the computation time is reduced by 62.4% and the memory occupation is reduced by 96.4%.

The relative pose estimation of the space target is indispensable for on-orbit autonomous service missions. Line segment detection is an important step in pose estimation. The traditional line segment detectors show impressive performance under sufficient illumination, while it is easy to fail under complex illumination conditions where the illumination is too bright or too dark. We propose a robust line segment detector for space applications considering the complex illumination in space environments. An improved two-dimensional histogram construction strategy is used to optimize the Otsu method to improve the accuracy of anchor map extraction. To further improve line segment detection’s effect, we introduce an aggregation method that uses the angle difference between segments, the distance between endpoints, and the overlap degree of segments to filter the aggregation candidate segments and connect disjoint line segments that probably came from the same segment. We demonstrate the performance of the proposed line segment detector using a variety of images collected on a semiphysical simulation platform. The results show that our method has better performance than traditional line segment detectors including LSD, Linelet, etc., in terms of line detection precision.

The existing methods for calculating electromagnetic scattering can be used to obtain the RCS of power lines. However, these methods do not take advantage of the periodicity of power lines. We propose a fast electromagnetic scattering calculation method combining the integral equation discontinuous Galerkin (IEDG) method and the characteristic modes-Sherman–Morrison–Woodbury algorithm (CM-SMWA) exploiting the power lines with stranded structure. We adopt the IEDG to discretize the electric field integral equation (EFIE) so that the EFIE can deal with non-conformal grids and significantly increase the flexibility of the CM-SMWA. Combing with the periodic property of power lines, the modeling and grid generation shall be carried out within one cycle (stranding) of the power line, and the grids of the rest cycle of the power line can be spliced by translating the grid of the divided sections. The advantage of the proposed method lies in that only the CM of one segment needs to be calculated, and the result can be applied to other segments to avoid repeated calculation of the CMs. The simulation results of the RCS of power lines show that the calculation time of our method is cut down by 50% as compared to the conventional CM-SMWA.

A novel power line detection method exploiting the Bragg point of power line is proposed in this paper. First, the radar echo of power line is divided into multi‐band along the frequency dimensional with incomplete repetition at equal intervals. Then, the candidate power lines in the echo of each frequency band can be found exploiting the Hough transform and constant false alarm rate (CFAR). Since the Bragg angle of the power line will change with frequency while that of the artefacts is fixed, the power lines can be easily detected from the background by exploiting unique frequency feature of Bragg angle of power line.