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.

With the continuous progress of satellite internet and China's aerospace TT&C technology, aerospace TT&C networks are developing towards intelligence and integration, making great progress in autonomous TT&C, resource allocation, and other aspects. Therefore, establishing an intelligent space-ground integrated network is an important goal for the future development of China's aerospace industry. In this paper, the relevant principles and technologies of tracking orbit, telemetry, and telecommand in intelligent space TT&C network are introduced. At the same time, combined with the space data link standard protocol proposed by CCSDS, TM, TC, AOS, Proximity-1, and USLP standards are introduced in detail, and the technology and practical application of different standards are analyzed. This paper introduces the working principle and technical requirements of space TT&C system from the view of the data link layer and physical layer, and provides reference and prospects for the research of the intelligent space-ground integrated satellite TT&C communication network in China.

This paper provides an overview of the current status and future trends in remote sensing satellite data transmission technology. The article begins by introducing the developmental history of remote sensing satellite data transmission. It then further elaborates on the technologies involved in remote sensing satellite data transmission, detailing key aspects such as data compression,data encryption, data framing, data encoding, data modulation, and data transmission. Subsequently the paper analyzes the challenges faced by remote sensing satellite data transmission, such as bandwidth limitations, signal processing, real-time requirements, and data handling. It also summarizes strategies to address these challenges, such as adopting laser-based data transmission, more complex modulation schemes, and multi-source fusion with computational transmission. Looking ahead, the paper envisions future trends, including inter-satellite laser relay transmission, on-board computational transmission, and the application of computational constellations for intelligent in-orbit fusion in remote sensing satellites. Research indicates that remote sensing satellite data transmission technology will evolve towards higher transmission rates, higher reliability, more convenient data processing, and more intelligent mission workflows.

The examples of foreign heterogeneous cooperative weapons projects and the forms of heterogeneous clusters are provided, and the definition of heterogeneous cluster is given based on the literature. Based on the process of multiagent cooperative warfare, four key areas of cooperative technology are summarized, including cooperative network communication technology,cooperative decision and planning technology, cooperative formation control technology, and cooperative terminal guidance technology. The key technologies in each area are summarized, and the technical differences between a heterogeneous cluster and a homogeneous cluster are given. On this basis, two technical areas are proposed, including pretask planning and cooperative game penetration guidance. The grouping and proportioning problem for heterogeneous cluster warfare is proposed, and the development status of scene modeling and bi-level optimization model solving technology is introduced. For the multiagent confrontation problem, the issues of using differential game theory are discussed. Finally, the difficulties faced by heterogeneous cluster cooperative technology are summarized, and the future development of this research field is prospected.

Clouds and precipitation are vital to the global water and energy cycle and act as crucial elements in maintaining the Earth's energy balance. Spaceborne cloud and precipitation radars can actively detect clouds and precipitation and obtain three-dimensional structural information of cloud and precipitation globally all day and night,effectively filling the shortcomings of pas-sive detection by meteorological satellites. Firstly, the demand analysis is conducted on spaceborne cloud and precipitation radars,summarizing the shortcomings of cloud and precipitation detection capabilities of current Chinese meteorological satellites. Then,the development status of spaceborne cloud and precipitation radars at home and abroad is introduced, and the problems that China's spaceborne cloud and precipitation radars need to be solved are summarized. Finally, we give the main direction of the development of spaceborne cloud and precipitation radars in China in the future.

With the increasing number of space debris and the increasing complexity of spacecraft missions as well as the requirements for adaptability to extreme environments, the operational status, damage diagnosis, life prediction and reliable safety as-sessment of spacecraft structure are particularly important. Operating as an effective approach, spacecraft structural health monitoring obtains structural feature information through sensor systems deployed in the structure，analyzes and evaluates the structural status through algorithm processing, thereby ensuring the safe and stable operation of the spacecraft at all stages. This paper focuses on the key technologies of spacecraft structural health monitoring. Firstly, from the sensor end of information acquisition, the technical characteristics, application status, current problems and development directions of optical fiber sensing, acoustic emission sensing and surface acoustic wave sensing are reviewed. Then, the research progress of sensor deployment methods and diagnostic evaluation algorithms for information processing is introduced. Secondly, the development trends and main challenges of spacecraft structural health monitoring are summarized and prospected.

This paper analyzes the four anytime requirements for LEO remote sensing satellites to realize all-time online. In order to adapt to the practical needs of flexible operation and rapid response of the satellites, it proposes a plan to carry out space-based TT&C based on the Tiantong-1 high-orbit mobile communication satellite. It also compares and analyzes the characteristics of various TT&C methods. The paper puts forward some assumptions,such as constructing the space-based integrated TT&C service system, developing the multi-method integrated TT&C terminal, optimizing the remote sensing satellite classification and operation strategy, and analyzes the overall feasibility. It explores a development path for realizing all-time online and anytime control application of LEO remote sensing satellites.

Existing deep learning-based modulation recognition methods are difficult to adapt to HF channels with significant time-varying characteristics, limiting their application in modulation recognition for High Frequency (HF) signals. In addition, in non-cooperative HF communication scenarios, the training dataset is often difficult to cover all possible modulation types, so that open-set modulation recognition also has important practical significance. This paper proposes a multi-modal feature fusion-based open-set modulation recognition method by combining communication domain knowledge and open-set recognition techniques,which effectively reduces the impact of time-varying HF channels and unknown modulation types on recognition performance. The proposed method first utilizes communication domain knowledge to obtain multimodal features that are robust to channel variations,and then extracts discriminative deep feature representations through multimodal feature fusion and deep feature learning to effectively identify known and unknown modulation types. In addition, the method also generates dummy samples through manifold mixing strategy to assist network training, which can enhance the network's ability to identify unknown types. Experimental results indicate that the proposed method outperforms existing open-set modulation recognition methods. When the channel conditions of training and testing signals are the same, the proposed method improves by over 3% in open-set recognition performance. When the channel condition of testing signals is drastically changed, that is, the channel conditions of the training and testing signals are different,the proposed method improves by over 8% compared to existing method, which exhibits strong robustness to channel variations.

With the swift advancement of radar jamming techniques, the variety of active jamming types and the diversity of jamming strategies have surged, urging for accurate identification of jamming types. Conventional active jamming identification methods lack efficiency and universality. Meanwhile, current deep learning-based approaches are encumbered by large-scale parameters and the need for extensive data, which significantly limit their practical applications. To enhance recognition capabilities under conditions with limited parameters and data, a lightweight few-shot radar active jamming identification method based on multi-modality fusion is proposed. Lightweight fusion is achieved by leveraging the temporal locality of time-frequency features and the high-resolution range profile features. Additionally, few-shot classification performance is improved through exploiting metric learning and feature retrieval techniques. Experiments conducted on both simulated and measured datasets demonstrate the superior performance of the proposed method under a variety of conditions.

This paper delves into the applications and the technological advancements of silicon-based analog beam- forming chips in high-frequency, high-bandwidth communication and phased-array radar systems. The context of 5G and the prospective 6G networks, which impose increasingly stringent demands on data transmission rates, anti-interference capabilities, and signal quality, So beam-forming technology has emerged as a pivotal factor in enhancing the performance of both communication and radar systems. Initially, this paper expounds on the fundamental principles of silicon-based analog beam-forming chips, highlighting their distinctive advantages in terms of low power consumption, high integration, and precise beam control. Moreover, it explores in depth exploration of the strategies for optimizing the silicon-based material processing techniques to improve frequency response and bandwidth handling capabilities. Subsequently, the paper elaborates on the key technologies embodied in silicon-based analog beamforming chips, including attenuators and phase shifters. Conclusively, the paper offers a forward-looking perspective on the future development trends of silicon-based analog beam-forming chips. Particular emphasis is placed on discussing the potential of technologies such as adaptive beam-forming, low-latency control, multi-functional integration, and the application of novel materials. The novelty of this research lies in the introduction of beam isolation technology, and the proposition of a viable approach to enhance frequency response and bandwidth processing capabilities through the optimization of silicon-based processes. This contributes to providing essential technical support for future wireless communication and radar systems.