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

共 4468 条记录，以下是61-70 订阅

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Research on calibration method of vehicle sensor based on C-V2X 4

Research on calibration method of vehicle sensor based on C-...

引用

4th International conference on Internet of Things and Smart City, IoTSC 2024

作者： Wang, Fengjiao Zhang, Ying Fu, Yanhong Huang, Yunliang Zhang, Dongze CATARC Intelligent and Connected Technology Co. Tianjin China

ISBN: (纸本)9781510681767

The stability and reliability of vehicle sensor data such as high-precision integrated inertial navigation system (INS), millimeter wave radar (MMW), laser radar (LIDAR) are very important for the functional realization of vehicle ADAS. Due to the influence of natural environment and working environment, the perception data of the sensor may be biased. C-V2X uses the characteristics of interconnection to collect and analyze the information of traffic participants such as vehicles and pedestrians in the surrounding environment and the roadside information such as map information, and broadcasts it to the surrounding vehicles to provide traffic environment reference data for the test vehicles. In general, the calibration of sensors requires additional calibration equipment. In this paper, the C-V2X transmission data of vehicle networking is used as the truth value system to provide reference data for the real-time calibration of vehicle sensors, which can reduce the test hardware equipment, and the truth value system works steadily, providing the location information of objects with high accuracy. This calibration method can improve the accuracy of vehicle sensor, and provide reliable data support for multi-sensor fusion and system calibration. © 2024 SPIE.

关键词： Inertial navigation systems

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Accurate Vital Sign Extraction by Variational Nonlinear Chirp Mode Decomposition

Accurate Vital Sign Extraction by Variational Nonlinear Chir...

引用

2024 Cross Strait Radio Science and Wireless technology conference

作者： Ruan, JunKai Li, Aojie Du, DaMing Oian, Zhengfang Zhu, Hua Shenzhen Univ Coll Phys & Optoelect Engn Shenzhen 518060 Peoples R China Shenzhen Univ State Key Lab Radio Frequency Heterogeneous Integ Shenzhen Peoples R China Key Lab Optoelect Devices & Syst Minist Educ & Gu Shenzhen 518060 Peoples R China

ISBN: (纸本)9798331507800;9798331507794

This study utilizes the Texas Instruments AWR1642BOOST 77 GHz millimeter-wave radar module to collect raw radar data. An All-Phase FFT is performed in the fas-time dimension to execute range FFT and obtain the complete phase signal. The arctangent algorithm is applied to identify the range bin corresponding to the human target and extract phase information. The phase signal is then demodulated and differentiated. The demodulated phase signal is separated using the Variational Nonlinear Chirp Mode Decomposition (VNCMD) algorithm. Compared to traditional methods (band-pass filtering, EMD, VMD) for processing respiration and heartbeat signals, the proposed algorithm demonstrates superior accuracy, validated against reference signals from the Texas Instruments ECG sensor ADSI292R.

关键词： FMCW radar Variational Nonlinear Chirp Mode Decomposition Vital Sign Millimeter Wave radar

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Subcarrier and Power Allocation Optimization Strategies for Full-Duplex DFRC System 24

Subcarrier and Power Allocation Optimization Strategies for ...

引用

11th International conference on Wireless Communication and sensor Networks (icWCSN)

作者： Xu, Zhan Qu, Hongsheng Yang, Xiaolong Beijing Informat Sci & Technol Univ Minist Educ Key Lab Modern Measurement & Control Technol Minist Informat IndKey Lab Informat & Commun Sys Beijing Peoples R China

ISBN: (纸本)9798400709005

Full-duplex communication and dual-function radar communication (DFRC) techniques are considered as key solutions to cope with the scarcity of spectrum resources in the wireless environment. This study investigates the optimization of subcarrier selection and system power allocation in a full-duplex DFRC system that meets predefined radar performance requirements to maximize the communication data rate (CDR). Specifically, under preset performance constraints, the system sequentially selects the most suitable sub-carriers for radar and communication and maximizes the CDR of the multicarrier DFRC system by optimizing power allocation. Then, by combining cyclic minimization algorithm, Karush-Kuhn-Tucker optimality conditions and water-filling power allocation algorithm, we designed an effective method for dividing and solving the above problem. Finally, several numerical simulation results are provided to verify the theoretical conclusions and validity of the proposed optimization strategy.

关键词： Dual-function radar communication system full-duplex communication communication data rate

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Three-Dimensional Cooperative Localization Based on Active radar/Infrared at Different Sites 2

Three-Dimensional Cooperative Localization Based on Active R...

引用

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

作者： Qian, Jialun Wang, Linhai Zhou, Shenghua Gong, Min Zhao, Pengfei Yang, Jian Sui, Xin Xidian University National Key Laboratory of Radar Signal Processing Xi'an China China Academy of Launch Vehicle Technology Beijing China

ISBN: (纸本)9798331515669

Multi-source perception fusion positioning technology based on heterogeneous sensors is a key research area in the field of target positioning. The heterogeneous sensor positioning system composed of radar and infrared has a wide range of applications. However, existing works mostly use radar measurement to expand the dimension of infrared data to locate target, which will introduce the large angle measurement error of radar into infrared. In this paper, we propose a radar/infrared linear weighted least-squares (WLS) localization algorithm based on target motion model. First, we build linear equations of target position relative to radar and infrared based on the space relationship, respectively. In this manner, the position of target can be solved through a linear optimization problem. Two kinds of equations are combined by deformation and solved by WLS algorithm to achieve the target localization. Simulation results show that the proposed method has better target localization performance than that of single radar, and with the improvement of the measurement accuracy of radar/infrared sensors, the localization effect is better. © 2024 IEEE.

关键词： radar measurement

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LiDAR and IMU Inertial Guidance Combined Navigation Front-End Design 2nd

LiDAR and IMU Inertial Guidance Combined Navigation Front-En...

引用

2nd International conference of Mechanical System Dynamics, ICMSD 2023

作者： Zhang, Xu Rao, Zixuan Yang, Fufeng Liang, Jiahao National Key Laboratory of Complex Multibody System Dynamics Institute of Launch Dynamics Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9789819980475

The combination of laser radar and IMU inertial navigation technology can establish a real-time point cloud map of the vehicle’s surrounding environment. The combination of navigation technology can accurately restore the external environment of the tank. Even in the dark and harsh weather conditions, the observer can effectively observe the external environment of the tank. For internal sensors, IMU inertial navigation can monitor the acceleration and angular velocity information based on the carrier’s motion status to obtain the carrier’s pose transformation state. Based on the tank-mounted multi-line laser radar as the hardware basis, research is conducted on algorithms such as data collection, matching, and pose calculation of laser point cloud data. This fusion positioning algorithm is based on the LeGO-LOAM algorithm for laser radar. The input source in the algorithm is laser point cloud data and the gyroscope data and accelerometer data of IMU inertial navigation. The laser radar sensor can obtain pose information through its own point cloud registration, and the IMU inertial navigation algorithm can obtain corresponding velocity and pose information through a strapdown navigation algorithm. The output information of IMU in the algorithm serves as the initial value for the laser radar sensor to solve the pose information. Through the ESKF algorithm, the updated laser radar data information and the real-time output information of IMU are fused to provide pose information for inter-frame registration of laser point clouds. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Optical radar

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An Adaptive Estimation Method for Group Target Number Based on Information Theoretic Criterion 2

An Adaptive Estimation Method for Group Target Number Based ...

引用

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

作者： Dou, Libin Jiang, Qi Wang, Rui Shi, Mengxin Zhang, Jichuan Beijing Institute of Technology Radar Technology Research Institute School of Information and Electronics Beijing China Beijing Key Laboratory of Real-Time Information Processing Technology of Embedded Beijing China Beijing Institute of Technology The Advanced Technology Research Institute Jinan China

ISBN: (纸本)9798331515669

The number of individuals within a group is crucial information for the correct association, robust tracking, and situation awareness. Traditional methods using the range profile's peaks are not suitable when targets are densely distributed. The target number estimation algorithms based on monopulse systems have high computational complexity, while those based on array systems require additional sensor resources. To address these issues, this paper proposes a method based on multiple incoherent observations using one monopulse radar. By combining multiple incoherent observations from a single sensor with information theoretic criterion, this approach can estimate the number of targets even when the resolution of a single sensor is insufficient. The effectiveness of the algorithm is verified through simulations, and the algorithm's performance is analyzed. © 2024 IEEE.

关键词： Monopulse radar

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Decomposition of Respiratory and Cardiac Rates Using Dual Band Distributed radar 21

Decomposition of Respiratory and Cardiac Rates Using Dual Ba...

引用

21st European radar conference, EuRAD 2024

作者： Choi, I. Park, S. Kim, M. Cha, S. Jin, Y. Bae, J. Hyun, E. Pukyong National University Department of Smart Mobility Engineering Korea Republic of Pukyong National University Department of Electronic Engineering Korea Republic of Korea Institute of Ocean Science and Technology Department of Maritime ICT and Mobility Research Korea Republic of DGIST Department of Automotive Technology Korea Republic of

ISBN: (纸本)9782874870798

Respiratory and cardiac rates can be estimated by analyzing a spectrum of phase modulation in a radar echo of an individual. However, the phase modulations corresponding to respiratory and cardiac rates are linearly mixed in a radar echo, so cardiac rate estimation is significantly difficult because of high order harmonics of a respiratory rate. We exploit independent component analysis (ICA) method for effective decomposition of respiratory and cardiac rates with a dual band distributed radar. In simulations and experiments, the respiratory and cardiac rates were successfully estimated by proposed decomposition method, compared with conventional methods. © 2024 European Microwave Association (EuMA).

关键词： Phase modulation

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Live Demonstration: Real-Time Gait and Respiration Analysis using Ultra-Wideband radar

Live Demonstration: Real-Time Gait and Respiration Analysis ...

引用

2024 Biomedical Circuits and Systems conference

作者： Chen, Ziwei Hadjipanayi, Charalambos Yin, Maowen Constandinou, Timothy G. Imperial Coll London Dept Elect & Elect Engn London England Imperial Coll London Care Res & Technol Ctr UK Dementia Res Inst London England

ISBN: (纸本)9798350354966;9798350354959

This paper presents a real-time algorithm developed for an ultra-wideband (UWB) radar sensor that performs comprehensive gait and respiration analysis. The method (1) estimates feet trajectory and respiration signals from radar data, (2) analyzes peak distributions and locations in the frequency spectrum, (3) identifies if either signal exhibits a sinusoidal waveform, (4) distinguishes between walking and pure breathing states based on signal characteristics, and (5) extracts clinically relevant features. The algorithm extracts spatiotemporal gait parameters for walking individuals, including step count, step length, cadence, and walking speed [1]. For stationary individuals, the system extracts the respiration rate along with a confidence level indicating whether the radar signal contains respiratory information or body-movement artifacts [2]. This demonstration highlights the potential of UWB radar technology as a dual-functional tool for continuous health monitoring applications, both in clinical and home environments. (Demo type: Academia) © 2024 IEEE.

关键词： Image segmentation

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Machine Learning based radar Heatmap Generation for Advanced Driver Assistance Systems 5

Machine Learning based Radar Heatmap Generation for Advanced...

引用

5th International conference on High Performance Big data and Intelligent Systems, HDIS 2023

作者： Klassen, Angela Karakuş, Erkan Yang, Qing Dept. of Electrical Computer and Biomedical Engineering University of Rhode Island KingstonRI02881 United States

ISBN: (纸本)9798350394160

radar sensors are commonly used in Advanced Driver Assistance Systems (ADAS) to detect surrounding objects. radar signals pass a signal processing chain to compute the range, the velocity and the angular position of potential obstacles and other traffic participants. Major challenges of this procedure are the high complexity and latency of transferring a large amount of raw radar data to subsequent processing units. This paper presents a machine learning model that dramatically reduces the latency of the data transfer by compression of the raw radar data and that generates Range-Angle (RA) Heatmaps directly from the compressed data. RA Heatmaps present the essential visualization technique for the localization of surrounding objects in the radar horizon. In addition, they can be used to detect and identify objects. We use the autoencoder and the U-Net architecture for the compression and the RA Heatmap generation respectively. For the collection of raw radar data, a Texas Instruments (TI) AWR1243 FMCW radar sensor board is utilized. The data to train the U-Net architecture is obtained by applying analytical radar imaging algorithms including a 3-dimensional Fast Fourier Transform (3D FFT) and our proposed framework for Region of Interest (ROI) extraction on the collected data. Experimental results indicate that our final system can achieve a significant reduction of the original raw radar data while still maintaining all relevant features required for object recognition tasks. Excellent accuracy scores exceeding 99 % on input data that has been compressed by a factor of four validate the capabilities of the model and underline its potential for radar data processing in the context of ADAS. ©2023 IEEE.

关键词： data transfer

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Interpreting Autonomous Driving Corner Cases: A Visual Analytics Approach 17

Interpreting Autonomous Driving Corner Cases: A Visual Analy...

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17th Pacific visualization conference (PacificVis)

作者： Sun, Yi Shao, Zekai Qiu, Xingyu Li, Yun Liu, Ting Xiang, Linbing Sun, Dong Chen, Siming Fudan Univ Shanghai Peoples R China NIO Shanghai Peoples R China

ISBN: (纸本)9798350393811;9798350393804

With the progression of artificial intelligence, there has been substantial advancement in autonomous driving technology. However, even the most advanced systems may confront failures in certain corner cases, necessitating enhanced analytical approaches. Traditional approaches focused on the numerical analysis of isolated sensor data, are often insufficient for deriving meaningful insights in such situations. To address this inadequacy, we propose a visual analytics approach, crafted to aid domain experts in performing analyses and extracting system improvements from cases with unexpected behaviors. This approach intricately integrates extensive driving scenarios and low-level module behaviors into the autonomous driving decision-making process, utilizing rich visualizations and an interface for interactive exploration and systematic synthesis of findings. Uniquely, our system opens the "black box" of modules in the decision-making pipeline during corner cases, taking into account both the overall decision-making pipeline and the fine-grained behaviors of the modules in the pipeline, setting our approach apart from previous works. To validate our system's effectiveness, we perform two case studies, inviting domain experts for evaluation, and the results confirm our system's efficacy in allowing experts to obtain crucial insights into autonomous driving systems.

关键词： Visual Analytics-data visualization-Interactive visualization Autonomous Driving-AD Simulations-Corner Cases

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