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检索条件"任意字段=Conference on Radar Sensor Technology"

共 5986 条记录，以下是261-270 订阅

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Distributed sensor Network for 3D Tag Localization Using Harmonic radar at 61/122 GHz ISM Band 20

Distributed Sensor Network for 3D Tag Localization Using Har...

引用

20th European radar conference, EuRAD 2023

作者： Hansen, Steffen Nowok, Sandra Shoykhetbrod, Alex Wickmann, Stefan Wessel, Jan Pohl, Nils Fraunhofer FHR Germany Ruhr-University Bochum Germany

ISBN: (纸本)9782874870743

In this paper, a study on the use of a harmonic radar at the 61/122-GHz industrial, scientific, and medical (ISM) frequency bands for 3D localization is presented. The radar is based on two self-designed monolithic microwave wave integrated circuits (MMIC) for the transceiver (TRX) and tag, which are fabricated in a 130-nm SiGe BiCMOS technology. The localization is carried out using the multilateration technique with four spatially distributed sensors. A simple calibration measurement was performed to determine the required sensor positions, which were then used to locate a tag with dimensions and weight of ≈ 2 cm3 / 9 g that can be mounted on the target. Despite strong interference caused by metallic fixtures, the positioning remains robust due to the harmonic radar principle. © 2023 European Microwave Association (EuMA).

关键词： Si-Ge alloys

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PETer: A lightweight human action recognition network based on millimeter-wave radar sparse point clouds 16

PETer: A lightweight human action recognition network based ...

引用

16th International conference on Signal Processing Systems, ICSPS 2024

作者： Sun, Kangsheng Jin, Biao Cai, Yan Li, Rongmin Jiangsu University of Science and Technology Ocean College Zhenjiang China Suzhou Zadar Vision Technology Co. Ltd. Suzhou China

ISBN: (纸本)9781510689251

Millimeter-wave radar, with its excellent environmental adaptability, high resolution, strong penetration capability, and privacy protection, is widely used in smart homes, elderly care, and security monitoring. However, due to the high sparsity of millimeter-wave point cloud data, it carries less information compared to video or LiDAR, posing significant challenges for precise and rapid human action recognition. This paper proposes a lightweight long-sequence spatiotemporal edge convolution Transformer network (PETer). The model first enhances the data, then separates the spatial and temporal information of the point cloud sequence, utilizes EdgeConv to capture the spatial geometric structure information of single-frame point clouds, and employs a Transformer to extract temporal features from the multi-frame spatial information. To validate the effectiveness of the model, this paper uses the IWR1443-ISK millimeter-wave radar as the detection sensor to capture human actions and generate a 3D point cloud dataset. This dataset covers 12 types of human actions from 7 volunteers, including walking, waving, boxing, and standing. The proposed model achieves an average accuracy of 98.50% on the dataset and 100% accuracy on the MARS human skeleton dataset. Compared to various point cloud networks, the PETer network is the smallest in size, fastest in speed, and highest in accuracy, demonstrating its superior performance in millimeter-wave radar human action recognition tasks. © 2025 SPIE.

关键词： Musculoskeletal system

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A Novel MIMO radar Waveform Design Method for Multi-Target ISAR Imaging 6

A Novel MIMO Radar Waveform Design Method for Multi-Target I...

引用

6th International conference on Electronics technology, ICET 2023

作者： Zou, Xuebo Jin, Guanghu He, Feng Zhang, Yongsheng National University of Defense Technology College of Electronic Science and Technology Changsha China

ISBN: (纸本)9798350337693

Inverse synthetic aperture radar (ISAR) is an advanced imaging sensor that can image moving air targets. Unlike mono-target imaging, due to the different motion parameters of multi-target, traditional ISAR imaging methods can't complete motion compensation for all targets simultaneously, which causes difficulties in their use for further applications. This paper proposes a novel MIMO radar waveform design method for multi-target imaging. Based on frequency spectrum matching, a waveform optimization model for multi-target imaging with constant modulus constraint is established, and is solved by an iterative optimization algorithm based on alternating projection methods. Simulation data are provided to illustrate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Iterative methods

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MWRC3D: 3D Object Detection with Millimeter-Wave radar and Camera Fusion 7

MWRC3D: 3D Object Detection with Millimeter-Wave Radar and C...

引用

7th International conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Wang, Ren Lu, Ningyun College Of Automation Engineerin Nanjing University Of Aeronautics And Astronautics Nanjing China Lianyungang Jari Electronics Co. Ltd Smart City Division Lianyungang China

ISBN: (纸本)9798350361445

sensor fusion has become an active research field due to its numerous advantages, such as improved perception capabilities, enhanced environment understanding, and better object detection and tracking performance. However, existing multi-sensors fusion models primarily concentrate on the combination of lidar and camera and neglect the millimeter-wave radar (MWR), an inexpensive and promising sensor. To address this limitation, this paper integrates camera and MWR, and proposes a novel framework called MWRC3D to achieve low cost and efficient 3d object detection. Specifically, we first propose an attention-based deep layer aggregation (ADLA) module for learning global associations and dependencies between individual pixels in an image, which improves the ability to characterize image features. Then, we introduce deformable convolutional networks (DCNs) to model geometric transformations, and a MWR data enhancement module is employed to correct 3D offset of radar point cloud from image center point. Finally, we stitch and fuse the image features with the radar feature maps as input to the quadratic regression head to obtain accurate 3D object detection boxes. To evaluate the effectiveness of the proposed model, extensive experiments are conducted based on the nuScenes dataset. The results demonstrate that the demonstrate that our method outperforms all baselines while maintaining high efficiency. © 2024 IEEE.

关键词： Object detection

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Evaluation criterion of space surveillance sensor scheduling based on relative orbit analysis 4

Evaluation criterion of space surveillance sensor scheduling...

引用

4th International conference on Electronic Communication and Artificial Intelligence, ICECAI 2023

作者： Shen, Jiakang Wang, Junling Zhao, Mengqi Lv, Peng School of Information and Electronics Beijing Institute of Technology Beijing China Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China

ISBN: (纸本)9798350314496

The rapid growth of the number of space targets leads to the shortage of sensor observation resources in the space surveillance network. Improving the efficiency of sensor scheduling helps to alleviate the observation pressure of the space surveillance network. In this paper, a unified observation model of space-based sensors and ground-based sensors for space targets is established based on the relative orbit of space targets. Based on the covariance matrix, a criterion function for calculating the scheduling efficiency of space surveillance network sensors is proposed, and the analytical solution of the scheduling criterion function under the assumption of plane circular orbit is given. The analytical solution can be used to analyze the influence of observation geometry, observation accuracy, observation times and other factors on scheduling efficiency. Finally, the influence of observation geometry on radar sensor scheduling efficiency is simulated and analyzed. The simulation results show that the orbit uncertainty decreases with the increase of the observation geometric angle under the same observation resources, therefore the radar sensor scheduling efficiency increases with the increase of the observation geometric angle. This conclusion is applicable to both space-based and ground-based radar sensors. © 2023 IEEE.

关键词： Covariance matrix

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Resilient Sparse Array radar with the Aid of Deep Learning 97

Resilient Sparse Array Radar with the Aid of Deep Learning

引用

97th IEEE Vehicular technology conference (VTC-Spring)

作者： Ahmed, Aya Mostafa Thanthrige, Udaya S. K. P. Miriya Sezgin, Aydin Gini, Fulvio Ruhr Univ Bochum Bochum Germany Univ Moratuwa Moratuwa Sri Lanka Univ Pisa Pisa Italy

ISBN: (纸本)9798350311143

In this paper, we address the problem of direction of arrival (DOA) estimation for multiple targets in the presence of sensor failures in a sparse array. Generally, sparse arrays are known with very high-resolution capabilities, where N physical sensors can resolve up to O(N-2) uncorrelated sources. However, among the many configurations introduced in the literature, the arrays that provide the largest hole-free co-array are the most susceptible to sensor failures. We propose here two machine learning (ML) methods to mitigate the effect of sensor failures and maintain the DOA estimation performance and resolution. The first method enhances the conventional spatial smoothing using deep neural network (DNN), while the second one is an end-to-end data-driven method. Numerical results show that both approaches can significantly improve the performance of MRA with two failed sensors. The data-driven method can maintain the performance of the array with no failures at high signal-tonoise ratio (SNR). Moreover, both approaches can even perform better than the original array at low SNR thanks to the denoising effect of the proposed DNN.

关键词： DNN Resilience sensor failures Sparse arrays sensing DOA

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Imaging experiments with a 340-GHz FMCW radar and frequency-diverse holograms 27

Imaging experiments with a 340-GHz FMCW radar and frequency-...

引用

conference on radar sensor technology XXVII

作者： Palli, Samu-Ville Tamminen, Aleksi Hiltunen, Paavo Rexhepi, Sazan Bonmann, Marlene Bryllert, Tomas Robertson, Duncan A. Ala-Laurinaho, Juha Stake, Jan Taylor, Zachary Aalto Univ MilliLab Dept Elect & Nanoengn Maarintie 8 Espoo 02150 Finland Chalmers Univ Technol Dept Microtechnol & Nanosci Terahertz & Millimetre Wave Lab SE-41296 Gothenburg Sweden Univ St Andrews Sch Phys & Astron St Andrews KY16 9SS Fife Scotland

ISBN: (纸本)9781510661844;9781510661851

We present recent developments of a standoff imaging system based on a frequency-diverse phase hologram and deep neural networks. The single-pixel imaging system operates in a monostatic configuration consisting of a 340-GHz FMCW radar and a frequency-diverse phase hologram to interrogate the radar down range direction with spatially varying, frequency-dependent field patterns. The measured back-reflected signal contains spatial reflectivity information from the target, and the fast chirp rate of the radar enables real-time imaging performance. Together with simultaneously acquired visible-light images, a deep neural network integrated into the submillimeter-wave data readout electronics can map the received signal onto a 2D image without mechanical or active electrical beam scanning. In experiments, we have collected submillimeter-wave and visible-light data of a moving target in the region of interest with a 60-Hz frame rate. The results suggest that the system can image the moving target with a resolution comparable to the theoretical diffraction limit. The minimal hardware complexity and good imaging performance of the demonstrated computational submillimeter-wave imaging system support its potential as a cost-effective and easily deployable solution for various imaging applications.

关键词： Hologram imaging FMCW radar neural network submillimeter-wave

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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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Development of Polarimetric radar Product and Initial Application for Airborne HIWC Detection 26

Development of Polarimetric Radar Product and Initial Applic...

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conference on radar sensor technology XXVI Part of SPIE Defense and Commercial Sensing conference

作者： Shrestha, Yunish Zhang, Yan Fusselman, Jakob McFarquhar, Greg M. Blake, WIlliam Harrah, Steven Univ Oklahoma Adv Radar Res Ctr Sch Elect & Comp Engn Intelligent Aerosp Radar Team IART Norman OK 73019 USA Univ Oklahoma Cooperat Inst Severe & High Impact Weather Res & Norman OK 73071 USA Univ Oklahoma Sch Meteorol Norman OK 73071 USA Garmin Int Inc Garmin Aviat Weather Radar Grp Olathe KS 66062 USA NASA Langley Res Ctr Hampton VA 23681 USA

ISBN: (纸本)9781510650930;9781510650923

Based on the previous development of available radar simulators, this work further evaluates the detection and estimation of High-Ice-Water-Content (HIWC) conditions for airborne radar sensing. In hardware development, we developed a new prototype X-band, dual-polarized planar broadside array for the system upgrade. We used the data from previous flight campaigns that combined radar and in-situ probe measurement to improve the physical models of the ice particles and their distributions. The usage of dual-polarized radar variables (such as ZDR and KDP) for forward-looking cases are then evaluated in parallel to the development of a new prototype of a low-cost airborne polarimetric radar sensor.

关键词： HIWC Aviation Hazards Airborne radar Sensitivity

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Fusing mmWave and RGBD sensor for Vitalsign Detection in Sleep and Respiratory Applications

Fusing mmWave and RGBD Sensor for Vitalsign Detection in Sle...

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2023 International conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Hsieh, Sheng-Hsien Tsay, Yuh-Jiuan Huang, Ya-Yun Chen, Yu-Wei Yu, Yu-Xuan National Pingtung University of Science and Technology Program of Artificial Intelligence and Mechatronics Pingtung Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung Taiwan

ISBN: (纸本)9798350324174

This paper proposes a dual-sensor fusion system that combines a Frequency Modulated Continuous Wave (FMCW) radar and an Intel RealSense RGB+Depth (RGBD) sensor as non-contact physiological signal sensing devices. Through the fusion of point clouds obtained from the dual-sensor system, the spatial information and vital sign signals can be perceived. © 2023 IEEE.

关键词： Frequency modulation

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