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High Degree of Freedom Low Coupling Sparse MIMO Array 7

High Degree of Freedom Low Coupling Sparse MIMO Array

引用

7th IEEE International Conference on Electronic information and Communication Technology, ICEICT 2024

作者： Yao, Yichang Pang, Baohe Li, Yingsong Yu, Canping Xiao, Wudang Li, Liping Zlatanov, Nikola Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China Innopolis University Faculty of Computer and Engineering Sciences Innopolis Russia

ISBN: (纸本)9798350384437

To achieve high precision direction-of-arrival estimation of MIMO arrays in highly coupled environments, based on the difference and cooperative array principles, the uniform array fitted with 5 base layer array and the uniform array fitted with 6 base layer array were used as transmitting arrays, and with the addition of 1 base layer layer sparse array as receiving array, two sparse multi-in multiple-out arrays were designed for single-base radar, which have the characteristics of low coupling of transmitting array and high freedom of receiving array. © 2024 IEEE.

关键词： Degrees of freedom (mechanics)

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Acceleration method for target HRRP generation based on DDPM 2

Acceleration method for target HRRP generation based on DDPM

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Shen, Xitai Zhou, Qiang Yu, Bingqian Zhang, Xin Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy of Intelligent Technology Zhengzhou450000 China Beijing Institute of Technology Radar Technology Research Institute Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

The target high resolution range profile (HRRP) is the sum of the vector projected on the radar line of sight of the target scatters, which can reflect the radial structure characteristics of the target and is one of the important means of radar target recognition. Existing HRRP-based target recognition methods adopt the idea of machine learning classification, which usually require sufficient training samples to obtain satisfactory recognition performance. To solve the dilemma of insufficient radar HRRP data caused by factors such as non-cooperative target and complexity of data acquisition process, this paper uses denoising diffusion probabilistic models (DDPM) to generate HRRP data. Furthermore, to solve the problem that the DDPM generation speed is too slow to meet the actual needs, this paper designs a fast DDPM HRRP (FDH) data generation method based on progressive knowledge distillation. Finally, the experimental results show that the generation speed is increased by about 25 times compared with the initial model under the premise of losing 7.6% similarity. © 2024 IEEE.

关键词： radar target recognition

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Transductive Multi-Prototype Network for HRRP Recognition with Missing Aspects 2

Transductive Multi-Prototype Network for HRRP Recognition wi...

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Yuan, Mingchen Liu, Jiaqi Wang, Xinyang Li, Yang Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy Of Intelligent Technology Zhengzhou450000 China Radar Technology Research Institute Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

The High-Resolution Range Profile (HRRP) plays a pivotal role in radar automatic target recognition. However, due to its aspect sensitivity, the absence of aspects within the training data can lead to a decline in recognition accuracy. To mitigate this issue, we introduce a novel Transductive Multi-Prototype Network (TMP-Net), leveraging the intrinsic similarity within test data to propagate labels along a manifold, thereby achieving classification. TMP-Net addresses the aspect sensitivity by utilizing multiple prototypes per class. Additionally, a loss function term is proposed to ensure the existence of the manifold. Experiments on the MSATR dataset demonstrate that TMP-Net outperforms existing methods by 10.22% in recognition accuracy even with only 10% of aspects represented in the training set. Furthermore, analysis reveals the advantages of employing multiple prototypes. © 2024 IEEE.

关键词： Automatic target recognition

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Improved Clutter Suppression Method for Bridge Vibration Measurement Based on GB-MIMO radar 2

Improved Clutter Suppression Method for Bridge Vibration Mea...

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Gao, Jiake Wang, Jian Wang, Siqi Qu, Xinran Li, Wenyu Deng, Yunkai Radar Technology Research Institute Bejing Institute of Technology Beijing China Beijing Building Research Institute Corporation Limited Cscec Beijing China Beijing Key Laboratory of Embedded Realtime Information Processing Technology Radar Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China

ISBN: (纸本)9798331515669

Ground based multi-input multi-output (GB-MIMO) radar has been gradually applied in the field of bridge vibration monitoring. During measurement, the interference of static clutter on the vibrating target signal in the same azimuth and range resolution severely affects the vibration measurement. The traditional method of removing static clutter is to estimate static clutter by fitting a circular curve to a complex signal point set, that is, fitting the vector of the circular curve center deviating from the origin of the polar coordinate system. Due to the clustered distribution of vibration points during non vibration time, the trajectory of complex sequence point sets will be distorted, resulting in poor clutter suppression effect. This article proposes an improved method for measuring the dynamic deflection of bridges by suppressing clutter. Firstly, obtain the vibration time period of the vibration candidate points through time-frequency analysis. Secondly, extract the complex sequence of each pixel during the vibration time period, and use the circular trace fitting method to estimate the stationary clutter. Then, based on outlier degree and outlier rate evaluation indicators, select vibration measurement pixels that can achieve effective clutter suppression. The effectiveness of this method was preliminarily verified by comparing the dynamic deflection curves of millimeter wave radar and laser vibrometer through model bridge experiments. In addition, the method was also validated through a high-speed railway bridge experiment. © 2024 IEEE.

关键词： Vibration measurement

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Joint Secure Transmit Beamforming Designs for Physical Layer Security in MIMO-ISAC System

Joint Secure Transmit Beamforming Designs for Physical Layer...

引用

signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Sitong Guo Hao Zheng Yinghui Zhang Junkun Yan College of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Inner Mongolia University Hohhot China National Key Laboratory of Radar Signal Processing Xidian University Xian China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

This article concentrates on the physical layer security (PLS) towards an integrated sensing and communication (ISAC) system, which communicates with legitimate communication users (CUs) and detects the single sensing target, which is considered to be eavesdropper because it might intercept the transmitting message from the base station to CUs. The joint transmitting beamforming for secure communication and sensing is designed to maximize the sum secrecy rate (SR) of system under the constraints of quality-of-service of CUs, the signal-to-Noise Ratio (SNR) of sensing and the power budget of the system. The optimal solution is obtained by the semidefinite relaxation and successive convex approximation algorithms. The availability of the beamforming design in ensuring the SR of the ISAC system is showed by Simulation results.

关键词： Array signal processing Simulation Quality of service Physical layer security Integrated sensing and communication Data processing MIMO Copper Optimization signal to noise ratio

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Multi-Terrain radar HRRP Target Detection Using Contrastive Learning 2

Multi-Terrain Radar HRRP Target Detection Using Contrastive ...

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Wang, Xinyang Yuan, Mingchen Liu, Jiaqi Li, Yang Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy of Intelligent Technology Zhengzhou450000 China Beijing Institute of Technology Radar Technology Research Institute Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information: Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

As radar resolution improves, high-resolution radars have significantly enhanced target detection performance through the generation of high-resolution range profiles (HRRPs). However, when the range resolution is much smaller than the target, the target's energy is dispersed across multiple range cells, leading to poor detection performance with traditional energy-based detection algorithms. Furthermore, existing detection algorithms are highly sensitive to clutter characteristics and exhibit poor adaptability to varying scenarios. To address these issues, this paper proposes a Constant False Alarm Rate (CFAR) HRRP detection algorithm based on contrastive learning for multiple terrains. The algorithm improves the contrastive learning loss function to achieve well-clustered representations of clutter samples during training. Test samples are evaluated by calculating the Mahalanobis distance between them and the training samples, and compared against detection thresholds to accomplish target detection. Testing results show that the proposed algorithm achieves superior detection performance across multiple terrains. Furthermore, to reach a 90% detection probability, the proposed method requires a signal-to-clutter ratio (SCR) reduction of 1 to 4 dB compared to the competing methods. © 2024 IEEE.

关键词： Clutter (information theory)

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Pulse train coding design for MIMO radar against interrupted sampling repeater jamming with Doppler frequency shifts

Pulse train coding design for MIMO radar against interrupted...

引用

signal, information and Data processing (ICSIDP), IEEE International Conference on

作者： Hao Wu Hao Zheng Yinghui Zhang Junkun Yan College of Electronic Information Engineering Inner Mongolia University Hohhot China Inner Mongolia Key Laboratory of Intelligent Communication and Sensing and Signal Processing Inner Mongolia University Hohhot China National Key Laboratory of Radar Signal Processing Xidian University Xian China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Intercepting and repeatedly retransmitting radar signals, interrupted sampling repeater jamming (ISRJ) generates higher power false signals that can seriously affect radar operation. To combat this interference, a scheme for countering ISRJ with Doppler frequency shifts by designing a multiple input multiple output (MIMO) radar with pulse train encoding and decoding is proposed. On the one hand, the scheme can suppress the pulse compression sidelobes of the target and ISRJ with Doppler frequency shifts. On the other hand, a detection matrix is designed to identify spurious peaks formed by interfering signals. Finally, the proposed scheme can accurately obtain target and jamming information in the environment while satisfying the constant mode (CM) constraints.

关键词： Hands MIMO radar Interference Repeaters Encoding MIMO Doppler radar Decoding Doppler effect Jamming

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Missing Modality Completion for Multi Frequency radar HRRP Recognition Using GAN 2

Missing Modality Completion for Multi Frequency Radar HRRP R...

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Zhou, Qiang Yu, Bingqian Meng, Yuanhao Zhang, Xin Li, Yang Wang, Yanhua Zhang, Liang Beijing Institute of Technology Zhengzhou Academy of Intelligent Technology Zhengzhou450000 China Radar Technology Research Institute Beijing Institute of Technology Beijing100081 China Beijing Key Laboratory of Embedded Real-Time Information Processing Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

High-resolution range profile (HRRP) is one of the commonly used methods in radar automatic target recognition (RATR). Recently, obtaining HRRP under different modalities, such as frequency and polarization, to improve the RATR performance has become an important development direction. However, in practical applications, sensor failures or interference may lead to modality loss during the model testing phase, resulting in decreased performance or even causing the model to fail to function properly. This paper primarily addresses the scenario of frequency modality loss and specifically proposes a modality completion and recognition network with generative adversarial network-embedded (MCRN-GAN) model. The model first generates and completes the missing modality features using the frequency feature transformation loop (FFTL) based on GAN. Subsequently, it fuses multi-modal features based on spatial and channel attention mechanisms to obtain a joint representation of dual-frequency features. Finally, a fully connected layer is used to complete the classification. Experiments on Ku and W frequency modality datasets demonstrates that the proposed method can effectively handle missing modality data after sufficient training without significant performance loss. © 2024 IEEE.

关键词： Frequency modulation

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Research on Dataset Preparation and Registration Methods for Multi-Temporal Airport SAR Images 2

Research on Dataset Preparation and Registration Methods for...

引用

2nd IEEE International Conference on signal, information and Data processing, ICSIDP 2024

作者： Wu, Guanghui Liu, Lujiao Li, Jianhao Pan, Hongxin Shi, Hao Beijing Institute of Technology Chongqing Innovation Center Chongqing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing China Beijing Institute of Technology National Key Laboratory of Science and Technology on Space-Born Intelligent Information Processing Beijing China

ISBN: (纸本)9798331515669

Synthetic Aperture radar (SAR) offers high-resolution imaging capabilities that are unaffected by weather and lighting conditions, making it ideal for complex environments. Recent advancements in spaceborne SAR technology have provided diverse high-resolution, multi-temporal SAR data, crucial for applications like airport monitoring. Despite these advancements, there is a notable lack of multi-temporal airport SAR datasets for research. This study addresses this gap by presenting a method to create a multi-temporal airport SAR image dataset. Utilizing known latitude and longitude information, the method converts geographic coordinates to image projection coordinates to locate airports in SAR images, followed by image conversion and alignment to construct the dataset. Additionally, this study introduces a registration method named SAR-SURF for multi-temporal SAR images, employing a SURF-based Feature Points Detector and an improved Fast Sample Consensus (FSC) algorithm. The experimental results demonstrate that this method effectively reduces speckle noise, ensures matching accuracy, and minimizes processing time, enabling rapid and precise registration of multi-temporal airport SAR images. © 2024 IEEE.

关键词： Image registration

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Vague Prototype-Oriented Diffusion Model for Multi-class Anomaly Detection 41

Vague Prototype-Oriented Diffusion Model for Multi-class Ano...

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41st International Conference on Machine Learning, ICML 2024

作者： Li, Yuxin Feng, Yaoxuan Chen, Bo Chen, Wenchao Wang, Yubiao Hu, Xinyue Sun, Baoling Qu, Chunhui Zhou, Mingyuan National Key Laboratory of Radar Signal Processing Xidian University Xi'an710071 China Xidian University Xi'an710071 China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China McCombs School of Business The University of Texas at Austin AustinTX78712 United States

Multi-class unsupervised anomaly detection aims to create a unified model for identifying anomalies in objects from multiple classes when only normal data is available. In such a challenging setting, widely used reconstruction-based networks persistently grapple with the "identical shortcut" problem, wherein the infiltration of abnormal information from the condition biases the output towards an anomalous distribution. In response to this critical challenge, we introduce a Vague Prototype-Oriented Diffusion Model (VPDM) that extracts only fundamental information from the condition to prevent the occurrence of the "identical shortcut" problem from the input layer. This model leverages prototypes that contain only vague information about the target as the initial condition. Subsequently, a novel conditional diffusion model is introduced to incrementally enhance details based on vague conditions. Finally, a Vague Prototype-Oriented Optimal Transport (VPOT) method is proposed to provide more accurate information about conditions. All these components are seamlessly integrated into a unified optimization objective. The effectiveness of our approach is demonstrated across diverse datasets, including the MVTec, VisA, and MPDD benchmarks, achieving state-of-the-art results. Copyright 2024 by the author(s)

关键词： Normal distribution

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