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Multi-component High-Frequency Vibration Error Estimation and Compensation Approach for Multirotor UAV SAR

IEEE Sensors Journal 2025年

作者： Han, Jiahao Tang, Shiyang Chen, Zhanye Guo, Ping Jiang, Chenghao Lian, Zhixin Zhang, Linrang Xidian University National Key Laboratory of Radar Signal Processing Xi’an710071 China Southeast University State Key Laboratory of Millimeter Waves Nanjing210096 China Southeast University Institute of Electromagnetic Space Nanjing210096 China Xian University of Science and Technology College of Communication and Information Engineering Xian710054 China

For multirotor unmanned aerial vehicle (UAV) synthetic aperture radar (SAR), the propeller rotation may lead to multi-component high-frequency vibration error (HFVE), seriously affecting imaging quality. To deal with this practical issue, a multi-component HFVE estimation and compensation approach is presented for multirotor UAV SAR, which can be implemented in three steps, i.e., vibration component extraction, vibration parameter estimation, and vibration error suppression. First, an improved ensemble empirical mode decomposition method is utilized to extract the vibration component of HFVE, ensuring the accuracy of component extraction. Then, based on the optimal solution of the correlation function, the parameters of the extracted vibration component are accurately determined to improve the accuracy of the constructed compensation function. Finally, all the vibration components are compensated in cyclic processing to achieve effective suppression of multi-component HFVE. Real data experimental results show that our approach outperforms the existing approach in terms of average impulse response width (0.21 m versus 0.25 m), peak sidelobe ratio (-25.26 dB versus -19.56 dB), and integration sidelobe ratio (-19.43 dB versus -6.54 dB), which verify the effectiveness of our approach. © 2001-2012 IEEE.

关键词： Drones

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A special type of the passive radar imaging using the self-multipath signals on satellites

A special type of the passive radar imaging using the self-m...

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IET International radar Conference (IRC 2023)

作者： Yi Zhou Ying Zhou Hui Ma Shenghua Zhou Yujie Zhang Haoran Sun Xue Wang Lin Liu Hongwei Liu National Laboratory of Radar Signal Processing Xidian University Xi'an People's Republic of China Beijing Institute of Remote-sensing Equipment Science and Technology on Millimeter-wave Laboratory Beijing People's Republic of China Institute of Information Sensing Xidian University Xi'an People's Republic of China

ISBN: (数字)9781837240982

This paper investigates the feasibility of observing the satellite by its own transmitted signals. The system is a special type of the passive radar (PR) using the self-multipath signal (SMS) on satellites. Firstly, the geometry of the SMS-based PR (SMS-PR) is formulated and analysed, and then the direct signals containing self-multipath are modelled. Secondly, the in-pulse matched filtering and the direct-path cancellation are individually considered and corresponding processing algorithms are given. Thirdly, the process algorithms are proposed of the SMS-PR imaging of the satellite, based on the inverse synthetic aperture radar (ISAR) and the orthogonal matching pursuit (OMP). Finally is the post-processing of the proposed scheme is verified by the simulation results. In addition, the paper analyses also the conditions guaranteeing the successful imaging.

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MP3Net:Multi-scale Patch Parallel Prediction Networks for Multivariate Time Series Forecasting

MP3Net:Multi-scale Patch Parallel Prediction Networks for Mu...

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International Joint Conference on Neural Networks (IJCNN)

作者： Daishun Cui Jiwei Qin Fang He Fei Shi Qiang Li Dezhi Sun Jiachen Xie School of Computer Science and Technology Xinjiang University Urumqi China Xinjiang Key Laboratory of Signal Detection and Processing Xinjiang University Urumqi China HongYou Software Co. Ltd Karamay China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Transformers have emerged as a crucial technology in long-term time series forecasting (LTSF). Recent studies have demonstrated that Transformers segment time series into patches, effectively capturing temporal patterns. However, single-scale patches still fail to adequately capture the complex short-term fluctuations and long-term trends in time series. To tackle this issue, we propose a novel framework, the Multi-scale Patch Parallel Prediction Network (MP3Net). Firstly, we propose a multi-scale patch module to extract local features and long-term correlations from the time series to effectively capture and identify data characteristics across different time scales. Secondly, we propose an adaptive fusion module to dynamically balance the weight of local detail features and long- term correlations from each branch. Thirdly, we introduce a hybrid loss function for model training aimed at enhancing the sensitivity and adaptability of the network towards different types of errors, consequently improving overall performance. Experiments conducted on five benchmark datasets demonstrate that MP3Net surpasses existing methods in LTSF and MP3Net presents an effective approach for addressing the challenge of modeling long-term dependencies in time series analysis.

关键词： Training Adaptation models Correlation Sensitivity Time series analysis Neural networks Transformers

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Distributed solving Sylvester equations with fractional order dynamics

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Control Theory and technology 2021年第2期19卷 249-259页

作者： Songsong Cheng Shu Liang Yuan Fan Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and AutomationAnhui UniversityHefei230601AnhuiChina Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical EngineeringUniversity of Science and Technology BeijingBeijing100083China

This paper addresses distributed computation Sylvester equations of the form AX+XB=C with fractional order *** partitioning parameter matrices A,B and C,we transfer the problem of distributed solving Sylvester equations as two distributed optimization models and design two fractional order continuous-time algorithms,which have more design freedom and have potential to obtain better convergence performance than that of existing first order ***,rewriting distributed algorithms as corresponding frequency distributed models,we design Lyapunov functions and prove that proposed algorithms asymptotically converge to an exact or least squares ***,we validate the effectiveness of proposed algorithms by providing a numerical example.

关键词： Fractional order calculus Distributed optimization Sylvester equation Frequency distributed model Convergence

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A 3D Wideband High-Gain Circularly-Polarized Array Antenna with Low RCS Using Simplified Sequential Rotation Topology

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Wang, Min Li, Xuan Ren, Yi Chen, Zhengchuan Zhao, Shiwei Chongqing University of Posts and Telecommunications School of Optoelectronic Engineering Chongqing400065 China Xidian University National Key Laboratory of Radar Detection and Sensing Shaanxi Xi'an710071 China Chongqing University School of Microelectronics and Communication Engineering Chongqing400044 China Guilin University of Electronic Technology Guangxi Wireless Broadband Communication and Signal Processing Key Laboratory Guilin541004 China

A 3D wideband high-gain circularly-polarized array antenna (CPAA) with low radar cross section (RCS) is presented in this manuscript. Its element contains four 3D radiation structures fed by a low-loss CP feeding structure and four polarimetric rotating-reflecting staircases (PRRSs) designed in a quasi-I shape. Radiation structure is designed as palm-leaf shaped radiator excited by a fan-shaped line and dispersive bilayer director for bandwidth enhancement. Current inversion method is realized by mirroring fan-shaped line to enable a 180° phase change to be compensated by CP feeding structure. Then, a simplified sequential rotation topology is realized to allow CP feeding structure to reduce loss and space occupancy, further enhancing gain and AR bandwidth. By rotating PRRS 90°, current inversion method is achieved to obtain 1-bit phase quantization. Finally, 16 identical elements with unequal phase states of any two adjacent PRRSs are cascaded by a 1-to-16 power divider. The measured results exhibit that a wide -10 dB impendence bandwidth of 32.8% and a gain of 21.1 dBi at 5.8 GHz are achieved. The 3-dB gain bandwidth reaches 31.9% while 3-dB axial ratio bandwidth is 26.7%. Moreover, the measured 10-dB RCS reduction band covers 5.1 GHz – 11.0 GHz. © 2002-2011 IEEE.

关键词： Circular polarization

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On the Performance of Uplink and Downlink Integrated Sensing and Communication Systems

On the Performance of Uplink and Downlink Integrated Sensing...

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IEEE Globecom Workshops

作者： Meng Liu Minglei Yang Arumugam Nallanathan National Laboratory of Radar Signal Processing Xidian University Xi’an China School of Electronic Engineering and Computer Science Queen Mary University of London London UK

ISBN: (纸本)9781665459761

We investigate an integrated sensing and communication (ISAC) system, where the full-duplex base station (BS) can serve the downlink (DL) and uplink (UL) communication Internet-of-Things (IoT) devices and detect targets simultaneously. As a further advance, non-orthogonal multiple access (NOMA) is taken into account to further improve the communication and sensing performances as well as the spectrum efficiency. The exact and asymptotic outage probabilities (OPs) of the DL and UL IoT devices are derived to evaluate the system performance for communication. Furthermore, the sensing performance is studied by deriving the probability of successful detection (PoD). The simulation results reveal that the proposed ISAC NOMA system outperforms the pure ISAC system in terms of the OP and PoD.

关键词： Performance evaluation NOMA Simulation System performance Probability Downlink Sensors

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Experimental analysis of sea clutter using airborne circular scanning SAR in medium grazing angle

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Journal of Systems Engineering and Electronics 2019年第1期30卷 68-77页

作者： PAN Xueli LIAO Guisheng YANG Zhiwei DANG Hongxing National Laboratory of Radar Signal Processing Xidian University Academy of Space Electronic Information Technology

The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the circular scanning synthetic aperture radar(SAR) has been applied to wide surveillance of the sea ***, the paper analyzes the validity of available sea clutter models for range Doppler images from different scan angles for moderate sea state in the medium grazing angle. The parameter estimation method for different distribution models employs the method of logarithmic cumulant(MoLC) based on Mellin transform uniformly. By the analysis of the fitting performance between the histogram of real data and the amplitude probability density function(PDF) of empirical distribution models and the goodness-of-fit(GoF) test for real data from different scan angles, it is indicated the generalized K(GK) distribution with generalized Gamma texture distribution can fit the sea clutter well for different scan angles in the medium grazing angle.

关键词： range Doppler image method of logarithmic cumulant (MoLC) Mellin transform generalized Gamma distribution.

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SSFam: Scribble Supervised Salient Object Detection Family

arXiv

引用

arXiv 2024年

作者： Liu, Zhengyi Deng, Sheng Wang, Xinrui Wang, Linbo Fang, Xianyong Tang, Bin Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China School of Artificial Intelligence and Big Data Hefei University Hefei China

Scribble supervised salient object detection (SSSOD) constructs segmentation ability of attractive objects from surroundings under the supervision of sparse scribble labels. For the better segmentation, depth and thermal infrared modalities serve as the supplement to RGB images in the complex scenes. Existing methods specifically design various feature extraction and multi-modal fusion strategies for RGB, RGB-Depth, RGB-Thermal, and Visual-Depth-Thermal image input respectively, leading to similar model flood. As the recently proposed Segment Anything Model (SAM) possesses extraordinary segmentation and prompt interactive capability, we propose an SSSOD family based on SAM, named SSFam, for the combination input with different modalities. Firstly, different modal-aware modulators are designed to attain modal-specific knowledge which cooperates with modal-agnostic information extracted from the frozen SAM encoder for the better feature ensemble. Secondly, a siamese decoder is tailored to bridge the gap between the training with scribble prompt and the testing with no prompt for the stronger decoding ability. Our model demonstrates the remarkable performance among combinations of different modalities and refreshes the highest level of scribble supervised methods and comes close to the ones of fully supervised methods. https://***/liuzywen/SSFam Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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Conditional Privacy-Preserving Transaction for the Unspent Transaction Output-Based Multi-Chain Blockchain System

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IEEE Transactions on Computers 2025年第07期74卷 2473-2486页

作者： Cui, Jie Zhuang, Wenting Zhong, Hong Zhang, Qingyang Wang, Fengqun He, Debiao Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Hefei230039 China Anhui University Anhui Engineering Laboratory of IoT Security Technologies Hefei230039 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China MatrixElements Technologies Shanghai Key Laboratory of Privacy Preserving Computation Shanghai201204 China

The anonymity of blockchain may be exploited by criminals for illegal fund transfers, thus a conditional privacy-preserving scheme is important for blockchain regulation. Currently, sharding technology under a multi-chain architecture is used to improve blockchain scalability. However, current conditional privacy-preserving schemes cannot work on this architecture. To protect the privacy of the transaction, we present a conditional privacy-preserving transaction scheme (MC-CPPT) for multi-chain blockchain system. In this system, we proposed a zero-knowledge proof based anonymous transaction, in terms of the identities of transaction participants and amounts, which also enables the unlinkability of transactions and indistinguishability between cross-chain and intra-chain transactions in multi-chain blockchain system. In addition, a multi-node regulatory agency is introduced to control the transaction amount and frequency in the system without a single point of failure. Moreover, an ECC-based encryption scheme is proposed to achieve the traceability of suspicious transactions. A security model is defined and the security of MC-CPPT is demonstrated to meet the expected security goals. Evaluating the prototype revealed acceptable performance and additional security features. © 1968-2012 IEEE.

关键词： Anonymity

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Exploring Multimodal Sentiment Analysis via CBAM Attention and Double-layer BiLSTM Architecture

arXiv

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arXiv 2023年

作者： Wang, Huiru Li, Xiuhong Ren, Zenyu Yang, Dan Ma, Chunming Xinjiang Key Laboratory of Signal Detection and Processing College of Information Science and Engineering Xinjiang University Urumqi China Xinjiang Multilingual Information Technology Laboratory College of Information Science and Engineering Xinjiang University Urumqi China

Because multimodal data contains more modal information, multimodal sentiment analysis has become a recent research hotspot. However, redundant information is easily involved in feature fusion after feature extraction, which has a certain impact on the feature representation after fusion. Therefore, in this papaer, we propose a new multimodal sentiment analysis model. In our model, we use BERT + BiLSTM as new feature extractor to capture the long-distance dependencies in sentences and consider the position information of input sequences to obtain richer text features. To remove redundant information and make the network pay more attention to the correlation between image and text features, CNN and CBAM attention are added after splicing text features and picture features, to improve the feature representation ability. On the MVSA-single dataset and HFM dataset, compared with the baseline model, the ACC of our model is improved by 1.78% and 1.91%, and the F1 value is enhanced by 3.09% and 2.0%, respectively. The experimental results show that our model achieves a sound effect, similar to the advanced model. Copyright © 2023, The Authors. All rights reserved.

关键词： Data fusion

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