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3rd International conference on Electrical, Electronics, and Information Engineering, EEIE 2024

作者： Lou, Jun Chen, Yingqing Yang, Jin Wang, Ling Hunan First Normal University Changsha410205 China

ISBN: (纸本)9781510688179

radar HRRP is easy to be obtained and contains rich target information. According to the scattering center theory, in the high frequency range, the target radar echo can be regarded as a superposition of several discrete and independent scattering center echoes. Extracting scattering center features from HRRP can be used for automatic target recognition. However, HRRP is generally complex value data, and traditional real-valued neural networks are difficult to process directly. To address this issue, this paper proposes a complex-valued neural network structure and designs the loss function based on the sparsity of the scattering center parameter space for HRRP scattering center extraction. Simulation experiments verify the effectiveness of the method. © The Authors.

关键词： radar theory

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Estimation of Water Surface Velocity Using FMCW radar with On-Chip Antenna

Estimation of Water Surface Velocity Using FMCW Radar with O...

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2024 Asia-Pacific Microwave conference

作者： Chen, Jintao Hung, Wing-Hung Wu, Ke-Li Chinese Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

ISBN: (纸本)9798350363555;9798350363548

This paper introduces a methodology for estimating surface water velocity utilizing Frequency Modulated Continuous Wave (FMCW) millimeter-wave (mmWave) radar technology operating at 60 GHz. The study leverages the IWR6843AOP radar sensor to obtain high-resolution data on water surfaces. By employing 1TX 1RX configuration, this method achieves an extensive beam width without compromising accuracy due to the specially designed algorithm for precise velocity estimation. This non-contact technique serves as an efficient and reliable alternative to conventional methods, offering enhanced safety and accessibility. Experimental results substantiate the efficacy of our approach, demonstrating significant promise for widespread application in environmental monitoring and water management systems.

关键词： Water flow velocity FMCW radar Millimeter-wave radar Surface velocity estimation non-contact measurement Signal processing algorithm Environmental monitoring Water resource management

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Analysis of sensor technology application in Chengdu: A case study of LiDAR 2

Analysis of sensor technology application in Chengdu: A case...

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2nd International conference on Digital Society and Intelligent Systems, DSInS 2022

作者： Deng, Fayun Wang, Jinhui Yu, Naiqi Tang, Min Library of Southwest Jiaotong University No. 999 Xi'an Road Pidu District Sichuan Chengdu China School of Public Administration Southwest Jiaotong University China School of Humanities Southwest Jiaotong University China

ISBN: (纸本)9781510663244

sensor technology is an important support for the development of intelligent manufacture, industrial Internet, smart city and other fields. As an important economic city in western China and the leader of Chengdu-Chongqing Economic Circle, Chengdu has long been planning and making arrangement in the sensor industry, which is supported by a large number of universities and scientific research institutes;This study searches "the laser radar in Chengdu" on incoPat patent analysis platform, and analyzes the application trend, applicants, technical field and patent operation data of the search results, so as to explore the advantages and disadvantages in the field of laser radar industry in Chengdu. Then it puts forward the corresponding strategies to promote the development of local sensor industry by improving the transformation and application of sensor achievements. © 2023 SPIE.

关键词： Optical radar

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Extraction of Ground Clutter Return Interference from Downward-Looking UWB radar Signal via Low-rank and Sparse Optimization 27

Extraction of Ground Clutter Return Interference from Downwa...

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conference on radar sensor technology XXVII

作者： Nguyen, Lam H. Ranney, Kenneth Kelly, Colin Gallagher, Kyle Le, Calvin Sherbondy, Kelly US DEVCOM Army Res Lab Adelphi MD 20783 USA

ISBN: (纸本)9781510661844;9781510661851

Ultra-wideband (UWB) ground-penetrating radar (GPR) technology has been widely employed for detecting underground targets, structures, or anomalies. However, the backscatter signals from the ground surface pose a critical challenge for downward-looking GPR systems since 1) these ground return signals have significant power compared to the backscatter signal from subsurface targets, and 2) the ground return and target signals completely overlap in both the time and frequency domains. This paper presents a technique for reconstructing and extracting the GRI signals from downward-looking UWB GPR signals. This simultaneous low-rank and sparse algorithm models the GRI signals as a low-rank matrix, while the return signals from the targets are represented by sparse signals. The solver simultaneously optimizes both objectives, resulting in the separation of the target signals from the GRI signals. Our technique performs this GRI extraction directly in the phase history data domain prior to synthetic aperture radar (SAR) image formation. Thus, it can be implemented as an additional step, completely independent from all other steps, in the pre-processing stage. Recovery results from both simulated and real data sets illustrate the robustness and effectiveness of our proposed technique.

关键词： UWB radar SAR GPR interference ground return sparsity sparse recovery noise-source separation

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A Multipath Signals Recognition Method based on Deep Neural Network 2

A Multipath Signals Recognition Method based on Deep Neural ...

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

作者： Chuanhao, Zhao Xu, Huang Jiamin, Long Mingxuan, Liu Xueyao, Hu Liping, Zhou Beijing Institute of Technology Radar Technology Research Institute Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (纸本)9798331515669

Millimeter-wave radar is the primary sensor for enabling autonomous driving and ADAS functions. MIMO technology has demonstrated its effectiveness to deliver precise angular estimation of objects using few antennas, making it a popular choice in automotive radar applications. However, a significant challenge for MIMO systems is multipath reflection. This phenomenon not only degrades angular estimation accuracy by disrupting the integrity of the virtual arrays in MIMO radar, but also impairs detection performance by introducing ghost targets. This paper addresses the issue of ghost target identification in multipath scenarios for vehicle-mounted MIMO radar. A method called DNN-IAA is proposed, which combines Iterative Adaptive Algorithm based on separation of sending and receiving (srt-IAA) with the Deep Neural Network (DNN) to tackle multipath signals recognition in complex scenarios. Firstly, srt-IAA is employed to obtain the two-dimensional angle-frequency spectrum of the target's Direction of Arrival (DOA) and Direction of Departure (DOD). Subsequently, the DNN is used to extract features from the DOA-DOD spectrum for the classification of multipath signals. Finally, a simulation is conducted to validate the proposed solution. © 2024 IEEE.

关键词： Adaptive algorithms

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Trajectory estimation with GNSS, IMU and LiDAR for terrestrial/kinematic laser scanning 28

Trajectory estimation with GNSS, IMU and LiDAR for terrestri...

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conference on Laser radar technology and Applications XXVIII

作者： Poeppl, Florian Pfennigbauer, Martin Ullrich, Andreas Pfeifer, Norbert Vienna Univ Technol Wiedner Hauptstr 8 Vienna Austria RIEGL Laser Measurement Syst GmbH Riedenburgstr 48 A-3580 Horn Austria

ISBN: (纸本)9781510661882;9781510661899

Kinematic laser scanning allows for efficient acquisition of large-scale and highly accurate 3D data. Georeferencing of the LiDAR data requires integration with auxiliary navigation systems. The standard processing pipeline consists of GNSS/IMU integration, georeferencing, and subsequent adjustment of the laser data. In contrast, we propose a holistic approach for GNSS, IMU and LiDAR integration where all measurements are incorporated in a single model, thereby enabling accurate estimation of both trajectory and system calibration parameters. This method is applied to the case of a 3D laser scanner mounted on a moving platform. We demonstrate precise georeferencing of the kinematically acquired data by comparison to statically acquired reference data.

关键词： Kinematic mapping sensor fusion sensor orientation in-run calibration

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Extrinsic Calibration of a Multiple radar System for Proximity Perception in Robotics

Extrinsic Calibration of a Multiple Radar System for Proximi...

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IEEE International Instrumentation and Measurement technology conference (I2MTC) - Rising Above Covid-19

作者： Ubezio, Barnaba Zangl, Hubert Hofbaur, Michael Univ Klagenfurt Inst Smart Syst Technol Klagenfurt Austria JOANNEUM RES Inst Robot & Mechatron Klagenfurt Austria

ISBN: (纸本)9781665453837

The simultaneous use of multiple small and low-cost radars has recently become feasible due to their increasing availability and functionality. Concerning the data fusion, computing the extrinsic parameters (rotation and translation) is a well known problem. However, the calibration of the sensor system is particularly challenging when dealing with devices having low number of antennas and therefore limited angular resolution, and there is currently no standard procedure for a setup consisting exclusively of such radars. This setup is though beneficial for collaborative and safety-oriented applications in robotics;therefore, we present an extrinsic calibration method for a multi-radar system deployed in a robotic cell. The calibration procedure only requires to move a single radar-signal reflector within the perceived area, without the need for additional sensing technology. The method is based on data sequential collection and pre-processing, combined with the closed-form registration of 3D point clouds. Furthermore, we include uncertainty information with the use of a custom MATLAB Toolbox1. Two different data collection procedures, inspired by a state of the art Motion Capture system, are presented and evaluated.

关键词： Robotics

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Research on Road Environmental Sense Method of Intelligent Vehicle Based on Tracking Check

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第1期24卷 1261-1275页

作者： Han, Yi Wang, Biyao Guan, Tian Tian, Di Yang, Guangfeng Wei, Wei Tang, Hongbo Chuah, Joon Huang Changan Univ Dept Automobile Xian 710064 Peoples R China Xian Univ Technol Dept Comp Sci & Engn Xian 710048 Peoples R China Univ Malaya Fac Engn Dept Elect Engn Block Y Kuala Lumpur 50603 Malaysia

Environment perception is the premise for intelligent vehicles to drive safely and stably. Despite the rapid development of road detection technology based on visual images, it is still challenging to robustly identify road areas in visual images due to the influence of illumination changes and noise. In order to solve this problem, we introduce a new optimized lidar and camera sensor fusion method for road environment sensing of intelligent vehicles. In road boundary detection based on laser data, a median point filtering method of ordered pole cloud is proposed. A method of boundary search, boundary seed point growth and obstacle clustering is proposed to identify road boundary. In the lane line classification based on visual image, a lane line search classification method is proposed, which can effectively classify lane lines and extract single lane lines. On the basis of the optimization of sensors, several constraint conditions are proposed based on the fusion of the two data, and the location of missing lane lines is predicted by using the road information identified by lidar and image, and the lane lines are identified again. Finally, a large number of experiments are carried out on kitti-Road benchmark data set, and a test platform is built to verify the results of the identification method proposed in this paper in rainy day, cloudy day, night and other special scenarios. Experimental results show that this method is superior to existing methods.

关键词： Roads Laser radar Intelligent vehicles Cameras Surface emitting lasers Sorting visualization Multi-sensor fusion intelligent vehicle environmental perception lidar machine vision

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Research on Time Synchronization and Spatial Calibration Algorithms of radar and Camera 2

Research on Time Synchronization and Spatial Calibration Alg...

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2022 2nd International conference on Detection technology and Intelligence System, DTIS 2022

作者： Song, Shiping Dong, Changqing Qin, Kongjian Hou, Xintian Zhao, Xiong Tian, Xiaodi Wang, HuaSen China Automotive Technology and Research Center Co.*Ltd Tianjin300300 China Company Limited Tianjin300300 China College of Cyberspace Security Nankai University Tianjin300350 China Beijing Jiaotong University Beijing100044 China

The intelligent connected vehicle can detect 360° full coverage around the vehicle by installing multiple radars and cameras. However, the sampling frequency of each sensor is different and each sensor outputs the target motion state information based on its coordinate system. the accurate and rapid realization of time synchronization and spatial position alignment between sensors is very important for multi-sensor data fusion. This paper presents a method of radar and camera time synchronization based on least squares cubic spline curve fitting. Based on time synchronization, a fast space joint calibration method of radar and camera is proposed based on the longitudinal symmetry plane of the vehicle. The validation data of the target object show that the proposed algorithm is accurate and simple. © Published under licence by IOP Publishing Ltd.

关键词： Cameras

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Monitoring sensor data in Real Time via Integrated IoT Platforms Using LoRaWAN technology 7

Monitoring Sensor Data in Real Time via Integrated IoT Platf...

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7th International conference on Devices, Circuits and Systems (ICDCS)

作者： Tamilarasi, Rubeena Grace Bala, G. Josemin Persis, Evangeline G. P. Moses, A. Andrew Seetharaman, A. Karunya Inst Technol & Sci Div Elect & Commun Engn Coimbatore India Karpagam Inst Technol Dept Elect & Commun Engn Coimbatore India Karunya Inst Technol & Sci Div Biotecnol Coimbatore India

ISBN: (纸本)9798350350470;9798350350487

The Internet of Things features a variety of platforms and software designed to enhance IoT device functionality. These platforms are tailored for specific tasks, optimizing performance within their domains. This study explores the integration of automation platforms with key elements like "Things Network" for LoRaWAN connectivity and "ThingSpeak" for data visualization. It examines different approaches for connecting these automation-based IoT platforms and studies their efficiency and performance. This study will bring in understanding of IoT technologies and platforms, unveiling their potential applications.

关键词： Virtuino MIT App Inventor IFTTT Power Bi ThingSpeak The Things Network Internet of Things Real time data Monitoring Integrated IoT Platforms LoRaWAN

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