The modulation spectrum processing of ship target radiated noise is an important means of detecting, tracking, and recognizing targets in naval operations. Improving the processing performance of modulation spectrum i...
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Space-Air-Ground integrated Vehicular Network(SAGVN)aims to achieve ubiquitous connectivity and provide abundant computational resources to enhance the performance and efficiency of the vehicular ***,there are still c...
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Space-Air-Ground integrated Vehicular Network(SAGVN)aims to achieve ubiquitous connectivity and provide abundant computational resources to enhance the performance and efficiency of the vehicular ***,there are still challenges to overcome,including the scheduling of multilayered computational resources and the scarcity of spectrum *** address these problems,we propose a joint Task Offloading(TO)and Resource Allocation(RA)strategy in SAGVN(namely JTRSS).This strategy establishes an SAGVN model that incorporates air and space networks to expand the options for vehicular TO,and enhances the edge-computing resources of the system by deploying edge *** minimize the system average cost,we use the JTRSS algorithm to decompose the original problem into a number of subproblems.A maximum rate matching algorithm is used to address the channel allocation and the Lagrangian multiplier method is employed for computational *** acquire the optimal TO decision,a differential fusion cuckoo search algorithm is *** simulation results demonstrate the significant superiority of the JTRSS algorithm in optimizing the system average cost.
This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution featu...
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This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction Network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.
With the development of informationtechnology,radio communication technology has made rapid *** radio signals that have appeared in space are difficult to classify without manually *** radio signal clustering methods...
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With the development of informationtechnology,radio communication technology has made rapid *** radio signals that have appeared in space are difficult to classify without manually *** radio signal clustering methods have recently become an urgent need for this ***,the high complexity of deep learning makes it difficult to understand the decision results of the clustering models,making it essential to conduct interpretable *** paper proposed a combined loss function for unsupervised clustering based on *** combined loss function includes reconstruction loss and deep clustering *** clustering loss is added based on reconstruction loss,which makes similar deep features converge more in feature *** addition,a features visualization method for signal clustering was proposed to analyze the interpretability of autoencoder utilizing Saliency *** experiments have been conducted on a modulated signal dataset,and the results indicate the superior performance of our proposed method over other clustering *** particular,for the simulated dataset containing six modulation modes,when the SNR is 20dB,the clustering accuracy of the proposed method is greater than 78%.The interpretability analysis of the clustering model was performed to visualize the significant features of different modulated signals and verified the high separability of the features extracted by clustering model.
To address the problem of sea clutter amplitude distribution characteristics varying with bandwidth, this paper obtains the raw data of clutter under different polarization methods of HH and VV in X and Ka bands based...
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In this paper, a high-gain 3d-printed phased array antenna is proposed for satellite applications. A multi-mode horn antenna is designed as the radiating element of the proposed phased array antenna. By optimizing the...
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In this paper, a type of low cross polarization phased antenna arrays for X-band spaceborne synthetic aperture radar (SAR) applications is presented. The horizontal polarization radiation performance is realized with ...
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In this paper, a data transmission communication payload for low-orbit satellite constellation is designed and implemented, which is used for bidirectional data transmission between satellites and ground. The payload ...
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The realization of phase shift or delay of antenna array beam control based on FPGA. The accurate phase delay control of an active electronic scanning array (AESA) benefits from the implementation of the field program...
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Autonomous underwater vehicles (AUVs) equipped with acoustic modems are currently one of the important means of obtaining underwater environment data such as sounds and images. They rely on high-speed underwater ...
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Autonomous underwater vehicles (AUVs) equipped with acoustic modems are currently one of the important means of obtaining underwater environment data such as sounds and images. They rely on high-speed underwater acoustic (UWA) communication technology for data transmission tasks. Orthogonal chirp division multiplexing (OCDM) is a multicarrier method based on chirp spread spectrum (CSS) which has better reliability in frequency selective fading channels than orthogonal frequency division multiplexing (OFDM). In this work, we combine index modulation (IM) and propose an OCDM-IM system that provides faster data rates when it activates the same number of subchirps as OCDM. On the other hand, it activates fewer subchirps when the data rate is the same, so it has better anti-interference capability. The simulation results under a measured UWA channel and random channels and the experimental results show that OCDM-IM has a better bit-error rate (BER) performance than that of OCDM and OFDM-IM systems when the subchirps are not fully loaded. In particular, when a small number of subchirps are activated, OCDM-IM is able to provide up to 2x bit rate with more than 5 dB improvement in BER performance. Our simulation and experimental results also show that IM has much better reliability than constellation mapping when Doppler effect is considered. Therefore, OCDM-IM is more suitable for the communication of AUVs. IEEE
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