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

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Human Activity Recognition using Low Cost Doppler radar sensor Network and CNN 9

Human Activity Recognition using Low Cost Doppler Radar Sens...

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9th International conference on Smart Computing and Communications, ICSCC 2023

作者： Deepthy, G.S. Peter, Keyaa Mathew, Edwin Thomas Bijoy, Meenakshy Jojo, Meenu Electronics and Communication Engineering Rajagiri School of Engineering and Technology Cochin India

ISBN: (纸本)9798350314090

Doppler radar sensor networks have gained increasing attention in human activity recognition due to their non-invasive nature and ability to operate in various environmental conditions. This technology has shown great potential in monitoring human activities such as walking, running, and even breathing. The Doppler radar sensors detect changes in the reflected signal caused by the movement of objects, including humans, and can provide valuable information about their movement patterns. In this abstract, we review the current state-of-the-art in Doppler radar sensor networks for human activity recognition which is low cost, non contact and privacy protected, highlighting the various signal processing techniques used to extract meaningful features from the raw data. © 2023 IEEE.

关键词： Doppler radar

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Compact X-band SAR pod for light UAVs and aircraft 15

Compact X-band SAR pod for light UAVs and aircraft

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15th European conference on Synthetic Aperture radar, EUSAR 2024

作者： Kant, Przemyslaw Stasiak, Krzysztof Rynkiewicz, Roman Krawiecki, Seweryn Gambrych, Jacek Wielgo, Maciej Ciania, Rafal Lech, Dominika Wiliński, Robert Samczyński, Piotr Kulpa, Krzysztof Michalski, Jerzy Julian SpaceForest Boleslawa Krzywoustego 1B Gdynia81-035 Poland Institute of Electronic Systems Faculty of Electronics and Information Technology Warsaw University of Technology Warsaw00-665 Poland XY-Sensing ul. Nowowiejska 15/19 Warsaw Poland

ISBN: (纸本)9783800762873

The paper summarizes the research, development, and first trials of a new compact synthetic aperture radar (SAR) system dedicated to unmanned aerial vehicles (UAVs) and light planes. The SAR sensor operates in the X-band with up to 2 GHz bandwidth. The system allows for online and offline data processing, achieving resolution finer than 15 cm (8 cm theoretical) in both range and cross-range. The radar system is also integrated with communication and navigation subsystems in a single pod weighing less than 10 kg. The SAR system has been successfully tested in flight trials mounted on a small aircraft. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Synthetic aperture radar

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Vehicle Trajectory data-Based Orientation Calibration for Two Oppositely Installed Roadside Millimeter-Wave radars: With and without Prior Road Alignment Knowledge 24

Vehicle Trajectory Data-Based Orientation Calibration for Tw...

引用

24th COTA International conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Li, Chengmin Wang, Junhua Fu, Ting Xue, Jiangtian Shi, Wenhua Key Laboratory of Road and Traffic Engineering Ministry of Education Tongji Univ. Shanghai China School of Computation Information and Technology Technical Univ. of Munich Munich Germany

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The cooperative operation of roadside millimeter-wave (MMW) radar sensors can effectively extend the detection range of a single unit through data splicing. However, accurate calibration of their positions is required as the foundation for data splicing. In this research, a novel framework is proposed, using trajectory data to calibrate the orientation of opposing roadside MMW radar. This approach takes advantage of overlapping detection regions to act as a "binding agent" in the calibration process. Considering practical constraints where prior alignment knowledge may be unavailable, two methods are developed that respectively mine radar data association through trajectory analysis for data splicing. These methods were applied to the roadside MMW radar data collected from the G94 highway. The calibrated trajectory plots confirm the successful establishment of data splicing between the opposing roadside MMW radar units using both proposed calibration methods. This research provides valuable insights for similar multi-sensor cooperative calibration tasks. © ASCE.

关键词： Roadsides

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Overview of SAR Image Fusion Processing Techniques with Other sensor data 25

Overview of SAR Image Fusion Processing Techniques with Othe...

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25th IEEE China conference on System Simulation technology and its Application, CCSSTA 2024

作者： Gao, Gemengyue Xin, Yu Li, Yingying Chen, Feng Feng, Xin Wang, Xueying Lin, Yuzhuoyue Zhou, Hongyuan Beijing Institute of Remote Sensing Information Beijing China

ISBN: (纸本)9798350366600

Synthetic Aperture radar (SAR), with its all-weather and all-day operational capabilities and wide-area detection ability, has become an important means for global monitoring of terrain and oceans. The fusion processing of SAR images with other sensor data can fully utilize the complementary advantages of information from various sensors to obtain richer and more targeted fusion results. This paper first analyzes and summarizes the SAR and opticalimage fusion processing techniques, including the main methods of pixel-level, feature-level, and decision-level fusion;then introduces the SAR and Automatic Identification System (AIS) data fusion processing technology, including data association methods based on location feature information and basedon multi-feature fusion, as well as ship fusion detection and recognition methods;finally, it summarizes the aforementioned methods. © 2024 IEEE.

关键词： Image fusion

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Comparative Study on various sensors for monitoring the Construction Sites

Comparative Study on various Sensors for monitoring the Cons...

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2024 International conference on Science, technology, Engineering and Management, ICSTEM 2024

作者： Gayathri, N. Gautham, B. Sarat Sethupathi, K. Saranram, K. Srinivasan, V. Department of Computer Science and Engineering Sri Eshwar College of Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350376913

Monitoring construction sites through sensor technology involves a structured approach to collect, transmit, and analyze crucial data for various aspects of the project. sensors are placed across the site to capture information on factors like temperature, humidity, vibrations, noise levels, and dust concentrations. These sensors transmit data wirelessly to a central monitoring system via IoT technology, which can be accessed remotely. The abstraction also allows for scalability and continuous improvement, creating a comprehensive framework for effective construction site monitoring and management. Monitoring construction sites using sensors has become an integral part of modern construction management. The first critical component is data Collection. The types of sensors included are temperature, humidity, vibration, noise level, and dust level sensors, which are strategically placed throughout the construction site. These sensors continuously capture real-time data, creating a robust foundation for monitoring and analysis. The second is the data Transmission component, that involves the seamless transfer of data from these sensors to a central monitoring system. The third is data visualization components that are used to display the readings that are taken by the sensors alternatively. The collected data is converted into user-friendly visualizations and dashboards. © 2024 IEEE.

关键词： data visualization

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radar Fault Detection via Camera-radar Branches Learning Network 5

Radar Fault Detection via Camera-Radar Branches Learning Net...

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5th International conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Ning, Dian Han, Dong Seog Kyungpook Natl Univ Sch Elect & Elect Engn Daegu South Korea Kyungpook Natl Univ Daegu Sch Elect Engn Daegu South Korea

ISBN: (纸本)9781665456456

radars are widely used in autonomous driving technology. Self-driving usually relies on radar signals to recognize pedestrians and vehicles, identify the surrounding environments reliably, avoid car crashes and navigation, and provide a reliable route to avoid collisions. The radar plays an important role in vehicle systems, and maintaining its proper functioning is necessary for the safety of self-driving systems to be considered. However, sensor faults are unavoidable. When the radar sensor is faulty, the radar signal will not receive the correct feedback information. Currently, it is hard to detect fault errors in radars, and the algorithm is complicated to work with. To analyze the radar cross section (RCS) signal and distance relationship, we used the RCS signal feature and combined the real-time features of the vehicle camera with the convolutional neural network (CNN) model to identify the fault information as expected. The paper uses a new data generator feature and deep learning model, recognizes the input signal as normal and abnormal, and the accuracy improves to 95.54%.

关键词： Anomaly Detection radar Cross Section(RCS) Convolutional Neural Network(CNN)

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Enhanced 2D-DOA Estimation for Monostatic EMVS-MIMO radar via Phase Compensation 2

Enhanced 2D-DOA Estimation for Monostatic EMVS-MIMO Radar vi...

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2nd IEEE International conference on Signal, Information and data Processing, ICSIDP 2024

作者： Zhang, Zhe Shi, Shuyun Wen, Fangqing China Three Gorges University College of Computer and Information Technology Yichang China National University of Defense Technology School of College of Electronic Countermeasure Hefei China

ISBN: (纸本)9798331515669

Multiple-input multiple-output (MIMO) sparse electromagnetic vector sensor (EMVS) arrays offer enhanced flexibility and resolution in signal processing. This study presents an improved PARAFAC-based algorithm for angle estimation in monostatic MIMO radar with arbitrary EMVS arrays. By leveraging the array data multidimensional structure and using PARAFAC decomposition for factor matrix estimation, followed by vector cross product and phase compensation techniques, the proposed method achieves super-resolution while maintaining low computational complexity. Numerical simulations confirm the superiority of the proposed method over existing algorithms. © 2024 IEEE.

关键词： Multistatic radars

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Infrared-radar multimodal target detection algorithm combining position prior information

Infrared-radar multimodal target detection algorithm combini...

引用

2023 International conference on Computer Graphics, Artificial Intelligence, and data Processing, ICCAID 2023

作者： Zhi, Xinkai Zhou, Hanqing Tang, Yang Avic Cape Beijing101400 China

ISBN: (纸本)9781510677685

In recent years, multimodal composite guidance technology has received extensive research and exploration, and multimodal fusion methods based on deep learning have achieved performance far superior to traditional methods. However, in practical applications, there are still many difficulties in the fusion technology of infrared images and high-resolution range profiles. In response to the above challenges, this paper fully utilizes the characteristics of sensor data collection to conduct in-depth research on the application of position prior, cross modal attention mechanism, and domain adaptation in multimodal object detection problems. A multimodal object detection algorithm called CenterNet- PK, which introduces a position prior, is proposed to deeply fuse infrared radar feature information while alleviating data heterogeneity issues. A feature extraction module based on one-dimensional convolution and bidirectional gated cyclic unit (Bi-GRU) was designed, and a radar feature map generation algorithm based on position prior was proposed. A cascade strategy was used to deeply fuse infrared and radar feature maps. Finally, the improved adaptive key point loss function was used to complete network training. The experimental results show that the proposed algorithm has high detection accuracy and anti-interference ability. © 2024 SPIE.

关键词： Object detection

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Neural Network technology of Mine Recognition Based on data From Magnetic Field sensors 12

Neural Network Technology of Mine Recognition Based on Data ...

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12th IEEE International conference on Intelligent data Acquisition and Advanced Computing Systems: technology and Applications, IDAACS 2023

作者： Peleshchak, Roman Lytvyn, Vasyl Peleshchak, Ivan Voloshyn, Serhii Lviv Polytechnic National University Department of Information Systems and Networks Lviv79000 Ukraine

ISBN: (纸本)9798350358056

Mine detection is an ongoing and growing problem that affects many people around the world due to the enormous danger that mines pose to humans. Mine detection occurs using various methods that use active sensors, including ultra-wideband (UWB) radar. Although active landmine sensors are often used for performance reasons, they can cause unintended landmine detonations because they operate on transmitted and reflected electromagnetic signals. Another way to detect mines without detonating mechanisms is the use of passive detectors. In this article, an optimal neural network structure with Adam's optimization algorithm is developed for effective mine classification based on magnetic field sensor data. This approach made it possible to increase the accuracy of mine detection to 99.23 percent. © 2023 IEEE.

关键词： Adam's optimization algorithm data preprocessing data visualization deep neural network passive mine detection

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Three-Dimensional Anti-Jamming Array Processing for GNSS-Based Navigational Aid Inspection 26

Three-Dimensional Anti-Jamming Array Processing for GNSS-Bas...

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

作者： Wolfley, Olivia Schvartzman, David Mansur, Brandon Fusselman, Jakob D. Zhang, Yan (Rockee) Snelling, Brad Univ Oklahoma Sch Elect & Comp Engn Intelligent Aerosp Radio Team Norman OK 73019 USA Univ Oklahoma Adv Radar Res Ctr Norman OK 73019 USA FAA AJF-13 Oklahoma City OK USA

ISBN: (纸本)9781510650930;9781510650923

We studied the technique and solutions of applying anti-jamming beamforming processing to the measured three-dimensional (3D) radiation patterns of GNSS antennas. We developed a small-scale, 2X3 custom array for demonstrating the GPS-L1 band operation. The process of measuring the 3D patterns is described. The visualization of individual and combined element pattern measurements serves as the basis for algorithm selections. The performance of anti-jamming post-processed beamforming and 3D pattern generation is evaluated using the measured pattern data. The technique and measurement process will be beneficial for the analysis of both civilian and military GNSS-based landing and navigational flight systems.

关键词： Manuscript format template SPIE Proceedings LaTeX

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