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.

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.

Aiming at the problem that the Siamese network has insufficient ability to express the features of scale-varying targets, a multi-branch structure is constructed by using convolution, pooling branches and pruning operations of different sizes to improve the robustness of features and ensure the translation invariance of the Siamese network. Aiming at the problem that the multi-branch structure brings too many parameters, the multi-branch structure is reparameterized into a single convolution in the tracking stage, which effectively reduces the time cost in the tracking stage. The experimental results show that compared with SiamFC, the accuracy, success rate and tracking speed of the proposed algorithm on the OTB100 datasets are improved by 5.1%, 3% and 30 FPS,respectively. The tracking accuracy and success rate are improved on the UAV123 and Temple-Color-128 datasets.

Hyperspectral target detection based on deep learning faces challenges such as insufficient quality of samples, intricate network structures, and laborious parameter adjustment. In this paper, we propose a deep learning method with data augmentation and automatic hyperparameter optimization. To tackle the issue of insufficient quality of samples, we introduce a sample augmentation strategy. The strategy utilizes endmember extraction and clustering techniques to directly acquire a large number of background pixels from hyperspectral images. By pairing these with a small number of known target pixels using a phase-reducing pixel pairing approach, we obtain a large number of labeled pure sample pairs, thereby accomplishing data augmentation. In addition, distinct from most complex deep networks, we designed a lightweight Convolutional Neural Network (CNN) comprised of 12 convolutional layers. This network is specifically engineered to efficiently and rapidly learn the mapping between input sample pairs and their corresponding labels. By incorporating the particle swarm optimization algorithm, this network possesses the capability to automatically optimize hyperparameters, overcoming the shortcomings of laborious parameter adjustment. This enables the network to automatically adjust hyperparameters based on samples from different hyperspectral images, thereby generating optimal results. For a test pixel, the input to the trained network is the spectral difference between the central pixel and its adjacent pixels. When a test pixel belongs to the target, the output score is closely align with the target label. Experimental results on five hyperspectral datasets demonstrate that our method significantly outperforms existing techniques.

Hailstorms are characterized by their suddenness, localized nature and high destructive power. Although observations acquired by ground-based automatic stations, radars and satellites play a certain role in hail identification, the limitation of single observation data leads to a high false alarm rate and low accuracy rate in hail identification. Therefore, there is an urgent need to construct a hail identification technology based on multisource high-resolution observation. In this paper, a multi-source data fusion network for hail recognition is proposed. The deep learning method utilizes the spatio-temporal feature extraction module, the multi-source data feature fusion module, and the UCUNet (U Connection Unet) recognition module to fully exploit the spatio-temporal features of the multi-source data such as FY4B (FengYun-4B star) satellites, weather radar, and numerical models when hail occurs, and innovatively adds the topographic height, slope, and slope direction as hail recognition factors. In order to evaluate the performance of the proposed network method, this paper conducts a series of experiments and compares the experimental results with real labeled data. The results show that HINet (Hail Identification Net) can make full use of multi-source data and effectively improve the hail identification results under complex terrain conditions. The network model proposed in this paper has high accuracy and practicality in hail research and identification.

Based on the requirements of space-based telemetry transmission of launch vehicle and the strict limitations of weight, space, and energy consumption on the vehicle platform, this paper designs a miniaturized, lightweight, highly integrated and low-power consumption S-band tile type active phased-array antenna system. The system includes antenna array module, T-module array module, power divider network module. beam controller and power unit module. The article elaborates on the working principle and integrated architecture of the system, and designs several key circuits such as antenna array, T-module, highly reliable power supply unit and beam controller, etc, according to the requirements. The developed antenna system prototype has been tested in a darkroom, and its major indexes such as beam width, axial ratio, ERIP within the beam scanning range of ±60°in the azimuth and elevation plane all meet the design requirements. Compared with brick phased array antenna systems with similar functions in the same frequency band currently on the market, its volume is reduced by 45%, weight is reduced by 25%, and the energy consumption is reduced by 15%, which is more in line with the phased array antenna from the arrow-carrying size, weight, and economic application demand. It also provides guidance for the development of phased array antenna in related fields.

According to the application environment of deep space laser communication, this paper analyzes the key performance indicators in the communication link. After taking into account factors such as distance spot diffusion attenuation, pointing control accuracy attenuation, atmospheric attenuation, solar radiation, detector dark current noise etc., this paper determines the specific calculation method of communication rate and communication bit error rate. Through formula derivation, the impact of the transmitter telescope diameter (laser beam divergence angle) and pointing control accuracy on the maximum communication distance is analyzed, and numerical simulation is used to support and further analyze the constraint relationships between transmitter telescope diameter (laser beam divergence angle) and pointing control accuracy and proposed design methods for the design of deep space laser communication links. The performance of laser links in the scenarios of earth-moon space and earth-Mars space under the existing laser communication capabilities is further calculated.

The reliability, security, and real-time of information transmission are crucial in defence application. Aiming at the problems that the useful information required cannot be accurately received in the battlefield environment with complex and strong electromagne-tic interference as well as multi-module integration, this paper creates a function, calculates the optimal value of the parameters through Monte Carlo experiments, and proposes a variable step size LMS adaptive beam forming algorithm based on elliptic function. Compared with other algorithms, the results show that the proposed algorithm is superior to the existing variable step size LMS algorithm in convergence speed under the premise of ensuring steady-state error, and the computational complexity is small. By simulating the interference signals of different incoming wave directions to draw the beam direction map, the simulation results show that this paper’s algorithm pointing strong, high interference suppression system, can achieve the effective reception of useful signals, effective suppression of interfering signals and equipment integration and miniaturization of the demand.

In recent years, with the development of new models of China's spacecraft and the advancement of the localisation process, considering the demand for highly integrated and remotely dynamically reconfigurable telemetry equipment, the development of remotely dynamically reconfigurable telemetry encrypted transmitters compatible with multiple modulation regimes is an inevitable trend in the development of telemetry transmission equipment. Differing from the traditional transmitter baseband software architecture of FPGA+DA+channel approach, the transmitter architecture consists of a heterogeneous multicore FMQL embedded system+RF integrated chip B9361 to form the transmitter baseband. This is combined with the software to achieve the functions of remote dynamically reconfigurable, poweron self-test, working status patrol, and real-time reporting of the working status. This improves the degree of integration of the measurement system and realizes the reconfiguration and sharing of the software and hardware resources to the maximum extent.It also significantly reduces the system volume, weight, power consumption, and cost. This scheme is based on the design ideas of generalization, serialization, and combination, so that the transmitter product has the advantages of high integration, serialization, and controllable components, generalized platform, flexible software configuration, etc. This provides strong technical support for the development of the new generation of telemetry transmitters in the direction of generalization, high performance, and dynamic reconfigurability.

The premission system calibration and tracking verification are important tasks to be accomplished by the Ka-band all-mobile integrated TT&C system, which has strong mobility, supporting the requirements of land mobile TT&C and maritime TT&C.The system is flexible in terms of station deployment location, and there is no calibration tower at the station deployment site,so it is impossible to use the traditional fixed calibration tower method for system calibration and tracking verification. The UAV platform is mobile and flexible, and after carrying Ka-band beacon machine and calibration zero inverter equipment, it can not only be used to complete the calibration phase, distance calibration zero and tracking verification work under the static condition of Kaband fully motorized comprehensive measurement and control system, but also meet the tracking verification demand under the system motorized measurement and control condition. In this paper, the UAV test calibration system is designed to meet the calibration and tracking verification requirements of Ka-band allmobile integrated TT&C system, and the tracking verification under maneuvering conditions is carried out.Through actual testing, the measurement accuracy of the mobile TT&C meets the requirements which provides a new means for the mobile TT&C,and has a good application prospect.

The new aerospace ground TT&C equipment adopts the virtual resource pool architecture and container cloud technology to carry out on-demand scheduling of measurement and control resources and generation of measurement and control business capabilities. The resource pool system contains a wide variety of heterogeneous resources, for which the signal processing resources are task-oriented scheduling requirements, this paper designs a signal processing resource scheduling strategy based on multilevel queue optimization for the resource pool, which aggregates the resources for management and unified allocation, and allocates and schedules them according to the task requirements in a hierarchical and optimal way to ensure the high availability of the resource pool system and the high utilization rate of resources.

Electromagnetic calculation and SAR echo simulation algorithm play an important role in radar system design, radar algorithm verification, and automatic target recognition algorithms research. To solve the problem of traditional electromagnetic calculation and SAR echo simulation algorithm being too time-consuming, an acceleration method for the entire process based on GPU is proposed. Firstly, the three core computing parts of the traditional algorithmray tracing, electromagnetic calculation,and SAR echo simulation are divided into multiple threads. Then, by using the GPU general computing platform, all thread units are processed in parallel to accelerate the simulation speed. Finally, the experimental results show that the acceleration ratio of this method is about 450 compared with singlecore CPU and about 50 compared to a 10-core CPU. This method achieves a good acceleration effect on the premise that the generated data is consistent with the traditional algorithm.

This article analyzes and verifies the reliability of high repetition rate narrow pulse width multi-wavelength lasers. A block diagram method model of high repetition rate narrow pulse width multi-wavelength lasers was established, and reliability analysis of the laser was conducted at the initial design stage. The reliability results of each unit of the laser were quantitatively calculated, including failure rate λ and Mean Time Between Failures (MTBF), with an expected MTBF of the entire laser system being 1 798.8 hours. To meet the design requirements of the laser, reliability optimization of the laser was achieved through selecting high-quality crystals, first-level derating design of semiconductor lasers, and redundant design of power control. After optimization, the MTBF of the entire laser system was increased to 2 260.9 hours. The reliability optimization design results of the laser system were validated, and the validation results showed that the laser's MTBF could reach 2 400 hours.

In response to the structural dynamics optimization design requirements of a certain satellite-borne precipitation radar, based on finite element analysis, the Kriging surrogate model is used to approximate the finite element model of the satellite-borne precipitation radar. The improved genetic algorithm is then employed to optimize the honeycomb panel structure parameters,resulting in a better design solution. Finally, the effectiveness of this method is demonstrated through a case study of the structural dynamics optimization design of a certain satellite-borne precipitation radar and mechanical experiments.

In this paper, an improved Surface Acoustic Wave (SAW) temperature and pressure sensor with two chambers is proposed to solve the nonlinear coupling problem in the integrated structure suggested in earlier studies, and the design and experimental study of an acoustic surface wave all quartz pressure sensor is carried out. Based on the finite element method and perturbation theory, the response mechanism of the quartz-based SAW pressure sensor is analyzed, the coupled mode theory is used to optimize the design of the three-resonator-type sensitive element, and the glass paste bonding is used to realize the quartz cross-lead hermetic encapsulation, and the preparation of the SAW allquartz pressure sensor is realized. The test results show that the developed SAW all quartz pressure sensor has a pressure range of 0~500 kPa, a linearity of 0.415% FS, a pressure sensitivity of 551 kHz/MPa, and a temperature coefficient of sensitivity of 0.134% over the operating temperature range of 0 ℃~120 ℃. The development of this surface acoustic wave all quartz pressure sensor lays the foundation for the subsequent realization of wireless passive measurement of the sensor.