The paper provides a brief overview of the development of terahertz technology and its advantages in various appli-cation scenarios, including high resolution and strong anti-stealth characteristics in radar. Regarding terahertz atmospheric transmis-sion characteristics, the paper focuses on the basic principles of the MPM and provides an overview and comparison of mainstream atmospheric transmission models like the ATM model and AM model. At the same time, this paper also introduces recent research developments and progress on terahertz atmospheric transmission characteristics domestically and internationally. Finally, this paper summarizes the development of terahertz technology and offers prospects for its applications.

DRO orbit in cislunar space is a kind of periodic orbit with great value and mission potential. The scientific exploration satellite on DRO orbit has the requirement of timely down-transmission of critical buret data of scientific payload and global coverage of measurement and control management. This paper analyzes the basic capability of BDS-3 global short message. The cis-lunar space TT&C data transmission scheme and TT&C data transmission process are designed based on the BDS-3 global short message, and the key technologies are analyzed. The research and analysis show that the cislunar space TI&C data transmission scheme based on the BDS-3 global short message can make up for the gap of ground-based TT&C, and realize the low-cost TT&C data transmission in all weather and all day.

Aiming at the issue of poor stability of visual localization and mapping (SLAM) methods during dynamic low-altitude flight of unmanned aerial vehicles (UAVs) in the absence of navigation signals, this paper proposes a UAV visual localization method based on edge features, which generates the edge features by downsizing the traditional feature extraction algorithm and finally completes the position estimation by nonlinear optimization. A convolutional neural network is employed to match edge fea-tures between consecutive key frames, yielding an edge feature reprojection error function, and finally the position estimation is com-pleted by nonlinear optimization. The experimental results demonstrate that compared to the state-of-the-art ORB-SLAM3 algo-rithm, the proposed method reduces localization time by 31% on the dataset and improves localization accuracy by 15.04% in low-texture scenes. Flight experiments further indicate a significant enhancement in the accuracy and stability of UAV localization.

The optical phased array controls the emission beam by adjusting the phase of the array antenna to change the wave-front, thus achieving control over the emission beam. Optical phased array technology has great potential applications in areas such as laser radar, laser communication, high-brightness laser generation, and synthetic aperture detection. This article reviews the re-search progress, advantages, and disadvantages of liquid crystal phased arrays, micro-electro-mechanical system phased arrays, and optical waveguide phased arrays. It also delves into the optical waveguide phased array technology in laser radar, proposing break-through directions for this technology.

Considering cost and integration constraints, traditional phased array antennas are usually single-polarized or time-multiplexed polarized and do not finely regulate the polarization form when transmitting or receiving signals, which constrains the polarization domain efficiency of phased array antennas. To address this issue, this paper is based on heterogeneous fully polarized phased arrays and jointly regulate their beam pointing and polarization parameters, in an attempt to achieve the full polarization ap-plication of phased array antennas at a lower cost. Firstly, the concept of heterogeneous fully polarized phased arrays is proposed;then, the mathematical model for the joint regulation of beam pointing and polarization parameters of heterogeneous fully polarized phased arrays is established; finally, a joint regulation method is proposed and mathematically simulated. The simulation results dem-onstrate the correctness and effectiveness of the joint regulation method for beam pointing and polarization parameters of heteroge-neous fully polarized phased arrays.

In order to achieve high-precision remote sensing inversion of suspended particulate matter concentration in the seas surrounding the Yellow River Estuary, this paper constructs seasonal models for spring, summer, and autumn, as well as a cross-seasonal model, utilizing GOCI-I image data and based on the WOA-BP algorithm. These models are compared with multiple algo-rithms such as Catboost, RF, KNN, BP and so on. The results reveal that within each seasonal model, the WOA-BP algorithm exhib-its superior performance on both the training and testing sets, with the average relative errors for the respective seasonal testing sets being 24.18%, 25.97%, and 29.42%. When the cross-seasonal testing set is employed to evaluate the three models, and their accura-cy is found to be significantly lacking, which indicates that seasonal models are not applicable across different seasons. In the cross-seasonal model, the WOA-BP algorithm again demonstrates the highest accuracy, with an overall average relative error of 26.96%. The average relative errors when testing with the three seasonal testing sets are 25.80%, 21.90%, and 37.17%, respectively. While the accuracy for summer is improved, the accuracy for the other two seasons falls below that of the corresponding seasonal models,with autumn experiencing the greatest decline in precision. Therefore, it is suggested that the cross-seasonal model be employed for spring and summer, whereas the appropriate seasonal models are recommended for autumn.

In recent years, as a crucial and fundamental task in applications such as autonomous driving, mobile robotics, and virtual reality, 3D object detection has received extensive attention from researchers in various fields. It aims to localize and classify objects of interest in 3D space and give the corresponding 3D bounding boxes, including the position, size, and orientation of objects, which provides the basic information for the subsequent understanding and perception of the 3D scene as well as planning and decision-making. Point clouds captured by LiDAR have become the most commonly used input data for 3D object detection due to their accurate 3D information and depth information. In this paper, the 3D object detection methods based on LiDAR point cloud with deep learning are reviewed, the characteristics and processing methods of point cloud are summarized, and several corresponding types of detection methods and multimodal fusion methods of point cloud and image are introduced. At the same time, this paper compares the performance of different methods and discusses the challenges and development trends of 3D object detection based on point cloud in the future.

In order to solve the networking communication problem of the main-subsidiary satellite cluster under discrete and sparse topology and to ensure the demand of real-time interactive remote control telemetry and task information between satellites,this paper proposes a set of communication system architecture and inter-satellite networking protocol stack design scheme according to the hierarchical and clustered spatial topology characteristics. Firstly, in the design of the network layer, the data structure of the network layer, the subnet cluster head selection backup mechanism based on the multi-weight priority cost function and the process of the sub-satellite network access are given respectively. Secondly, in the data link layer, the data is processed hierarchically according to the subcontracted remote control and subcontracted telemetry system. Then, in the design of the physical layer, the spread frequency hopping is used as the communication system of the inter-satellite link, and the time division multiple access method is used to realize the multi-user communication of the satellite cluster, and the specific communication index of the inter-satellite link is given. Finally, the link calculation of inter-satellite communication is carried out. The calculation results show that the physical layer design meets the communication requirements of each satellite.

Satellite resources on board are limited and precious, and ground terminals in real communication scenarios have different geographic distribution and satellite communication service demands, so dynamic on board satellite resource management is needed to design flexible and efficient resource management schemes. In this paper, the use of hopping beam technology can provide flexible resource management at the beam level to solve the problem of unbalanced service demand between ground cells covered by point beams generated by high-throughput satellites. Firstly, in order to solve the problem of co-channel interference in beamhopping satellites, an interference avoidance strategy between beam-hopping clusters based on frequency mode switching is proposed. Further, two cluster configuration strategies, uniform and non-uniform clustering, are proposed. In order to solve the problem of poor equalization effect of uniform clustering and unsuitable for the dynamic change of the ground, combined with the problem of co-channel interference, a non-uniform cluster configuration strategy based on frequency mode switching is proposed for the interference avoidance strategy between beam-hopping clusters. Finally, the interference avoidance strategy is verified and simulated. Besides,the different clustering strategies are verified based on various intelligent optimization algorithms. The simulation results verify the feasibility of the clustered configuration and show that the non-uniform clustering algorithm with no distance limitation has the strongest flow-balancing ability.

X-ray communication technology is a kind of space communication mode using X-ray as a carrier, which has the advantages of a large communication bandwidth, light weight, small volume, low power consumption, and high confidentiality. By designing a multi-target X-ray signal modulation device, the X-ray communication rate can be improved, and the accuracy of X-ray energy spectrum recognition at the signal receiving end can be ensured, so that the advantages of X-ray communication based on energy load can be truly played. In this paper, an X-ray communication demodulation method based on peaking multi-level support vector machine is proposed to accurately identify the X-ray characteristic energy spectrum of multi-target materials. A peaking multilevel support vector machine classifier suitable for four-element communication is designed. The parameter tuning and verification ensure high accuracy and generalization ability. The simulation results show that support vector machine provides an efficient, accurate, and robust signal recognition solution for X-ray communication based on energy load.