Digital channelization technology is often used for broadband electromagnetic signal reception. When its analysis filter banks and comprehensive filter banks have precise reconstruction characteristics,accurate reconstruction of the received signal can be achieved. For the electromagnetic spectrum recognition problem in the field of complex electromagnetic environment perception,it is necessary to accurately restore the electromagnetic signal received by the receiver and perform spectrum recognition based on the accurately restored signal. The article proposes an intelligent electromagnetic spectrum recognition technology based on precise reconstruction of digital channelization. Firstly, a digital channelized receiver structure that can achieve precise signal reconstruction is constructed. Then,wavelet analysis is used to construct a time-frequency waterfall diagram of the signal,and artificial intelligence processing is performed based on this graph to achieve electromagnetic spectrum recognition. Finally,simulation results are provided. The simulation results in the article demonstrate the correctness and effectiveness of the method.

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.

Image fusion model based on autoencoder network gets more attention because it does not need to design fusion rules manually. However, most autoencoder-based fusion networks use two-stream CNNs with the same structure as the encoder,which are unable to extract global features due to the local receptive field of convolutional operations and lack the ability to extract unique features from infrared and visible images. A novel autoencoder-based image fusion network which consist of encoder module, fusion module and decoder module is constructed in this paper. In the encoder module, the CNN and Transformer are combined to capture the local and global feature of the source images simultaneously. In addition, novel contrast and gradient enhancement feature extraction blocks are designed respectively for infrared and visible images to maintain the information specific to each source images. The feature images obtained by encoder module are concatenated by the fusion module and input to the decoder module to obtain the fused image. Experimental results on three datasets show that the proposed network can better preserve both the clear target and detailed information of infrared and visible images respectively, and outperforms some state-of-the-art methods in both subjective and objective evaluation. Meanwhile, the fused image obtained by the proposed network can acquire the highest mean average precision in the target detection which proves that image fusion is beneficial for downstream tasks.

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.

Compared to 32QAM technology, 32APSK technology reduces the number of amplitudes and is suitable for a nonlinear channel in a relay satellite communication system. TCM technology combines channel coding and multi-level modulation,doesn't increase the spectrum bandwidth, decreases the transmission power, cuts down energy consumption, lowers the requirements for technical indexes of the power amplifier, and is beneficial for achieving lightweight and miniaturization of satellite payloads. This paper combines 32APSK technology and TCM technology, proposes a kind of 32APSK-TCM technology, discusses details of the 32APSK-TCM technology constellation subset splitting method and constellation point selection method, and analyzes the performance of the 32APSK-TCM technology. This paper simulates the 32APSK-TCM technology and 16APSK technology using the simulation platform of the relay satellite communication system developed by our research team. Simulation results demonstrate that under the condition of an ideal channel, I/Q amplitude phase imbalance, amplitude frequency characteristics, group delay, phase noise, power amplifier saturation point, and nonlinear channel, if the maximization value of the required bit error rate is 1E-6, compared to 16APSK technology, the minimization value of the signal-to-noise ratio of 32APSK-TCM technology saves 13.29 dB, 13.29 dB, 14.84 dB, 15.54 dB, 15.11 dB, 15.77 dB, and 16.37 dB, respectively.

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.

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.

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.

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.

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.