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 discr...
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This paper introduces a methodology for estimating surface water velocity utilizing Frequency Modulated Continuous Wave (FMCW) millimeter-wave (mmWave) radartechnology operating at 60 GHz. The study leverages the IWR...
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ISBN:
(纸本)9798350363555;9798350363548
This paper introduces a methodology for estimating surface water velocity utilizing Frequency Modulated Continuous Wave (FMCW) millimeter-wave (mmWave) radartechnology operating at 60 GHz. The study leverages the IWR6843AOP radarsensor 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.
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 crit...
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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.
sensortechnology 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-Chon...
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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, m...
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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 pi...
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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.
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 ...
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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.
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 identif...
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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.
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 th...
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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 stud...
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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 datavisualization. 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.
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