The Millimeter-wave radar has become an important sensor for advanced driver assistance systems due to its advantages such as environmental adaptability, low cost and detection accuracy. Most of current vehicle radars...
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In this paper, we report the results of a radar and accelerometer based pilot observational study of gait patterns of elderly participants enrolled in an exercise program aimed at improving strength, balance, and agil...
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ISBN:
(纸本)9781510674158;9781510674141
In this paper, we report the results of a radar and accelerometer based pilot observational study of gait patterns of elderly participants enrolled in an exercise program aimed at improving strength, balance, and agility. We employ a radar system and a wearable accelerometer device to capture biomechanical movements of the participants as they walk back and forth in front of a radar. We extract gait parameters by analyzing the Doppler signatures obtained from the radar measurements and time-series data from the accelerometer device worn on the wrist while walking. Additionally, we record physical activity levels of participants over a two-week period using the wrist-worn accelerometer device and determine duration of moderate-to-vigorous physical activity (MVPA). The gait parameters and MVPA duration, extracted from two separate sets of measurements made prior to and at the conclusion of the exercise program, are used to assess potential changes in the gait and mobility of the participants. Using percentage change in parameter values as a metric, the results generally demonstrate a positive impact of the exercise program on gait and physical activity levels. At the same time, an appreciable categorical agreement is observed between the two sensing modalities.
This paper introduces a new approach for addressing the complex problem of Multi-target tracking in external radiation radar systems equipped with Multi-static Doppler measurements. Drawing from research on sensor arr...
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3D object detection aims to extract the spatial positions of objects from sensordata, thereby improving environmental awareness and comprehension. With the advancement of radartechnology, the 4D imaging radar offers...
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This research plunges into the rapidly growing radartechnology in the medical sector, putting emphasis on its possibility to revolutionize elderly care and health monitoring among the aging global population. Based o...
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ISBN:
(纸本)9781510674370;9781510674363
This research plunges into the rapidly growing radartechnology in the medical sector, putting emphasis on its possibility to revolutionize elderly care and health monitoring among the aging global population. Based on a systematic literature review and rigorous bibliometric analysis, we discuss radartechnology application in healthcare, focusing on its potential for non-invasive, high-accuracy diagnosis and continuous patient monitoring. Our findings highlight the critical harmony between radartechnology and the advances in machine learning, artificial intelligence, and data analytics, which open the door to smart healthcare solutions. These advancements will improve early disease detection, fall risk prevention, and real-time health monitoring, resulting in quick medical responses. This study endeavors to offer useful knowledge to researchers, practitioners, and policymakers who are working towards the use of technology for better health in the context of the demographic changes that the world is experiencing in terms of an ageing population by mapping the current research landscape, identifying the existing trends and gaps, and proposing the future direction of research.
The automotive industry is facing an unprecedented technological transformation towards fully autonomous vehicles. Optimists predict that, by 2030, cars will be sufficiently reliable, affordable, and common to displac...
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The automotive industry is facing an unprecedented technological transformation towards fully autonomous vehicles. Optimists predict that, by 2030, cars will be sufficiently reliable, affordable, and common to displace most current human driving tasks. To cope with these trends, autonomous vehicles require reliable perception systems to hear and see all the surroundings, being light detection and ranging (LiDAR) sensors a key instrument for recreating a 3D visualization of the world. However, for a reliable operation, such systems require LiDAR sensors to provide high-resolution 3D representations of the car's vicinity, which results in millions of data points to be processed in real-time. With this article we propose the ALFA-Pi, a data packet decoder and reconstruction system fully deployed on an embedded reconfigurable hardware platform. By resorting to field-programmable gate array (FPGA) technology, ALFA-Pi is able to interface different LiDAR sensors at the same time, while providing custom representation outputs to high-level perception systems. By accelerating the LiDAR interface, the proposed system outperforms current software-only approaches, achieving lower latency in the data acquisition and data decoding tasks while reaching high performance ratios.
With the continuous development of sensortechnology and electronic information technology, data fusion technology is of great significance in improving the system's ability of detecting, recognizing and tracking ...
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ISBN:
(纸本)9798350390780;9798350379228
With the continuous development of sensortechnology and electronic information technology, data fusion technology is of great significance in improving the system's ability of detecting, recognizing and tracking targets. That is, a single sensor can only provide partially imprecise information, thus not excluding ambiguity in the description of the external environment. Given the complementarity exhibited by the differences in the performance of the sensors, synthesizing the information from individual sensors results in more accurate and reliable information than a single sensor can provide. A multi-sensor fusion method based on extended Kalman is proposed to address this problem. Experimental results show that the accuracy and robustness of target detection and tracking can be significantly improved by the fusion of infrared and millimeter wave radardata.
This paper presents a comprehensive method for dataset construction, utilizing 3D object detection to automatically label objects detected by LiDAR sensors and synchronizing multi-sensor labeling through coordinate ca...
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The millimeter-wave radarsensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdoor mobile robotics. However, the rada...
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ISBN:
(纸本)9798350384581;9798350384574
The millimeter-wave radarsensor maintains stable performance under adverse environmental conditions, making it a promising solution for all-weather perception tasks, such as outdoor mobile robotics. However, the radar point clouds are relatively sparse and contain massive ghost points, which greatly limits the development of mmWave radartechnology. In this paper, we propose a novel point cloud super-resolution approach for 3D mmWave radardata, named radar-diffusion. Our approach employs the diffusion model defined by mean-reverting stochastic differential equations (SDE). Using our proposed new objective function with supervision from corresponding LiDAR point clouds, our approach efficiently handles radar ghost points and enhances the sparse mmWave radar point clouds to dense LiDAR-like point clouds. We evaluate our approach on two different datasets, and the experimental results show that our method outperforms the state-of-the-art baseline methods in 3D radar super-resolution tasks. Furthermore, we demonstrate that our enhanced radar point cloud is capable of downstream radar point-based registration tasks.
This study implemented a simulator for verification of a MIMO radar front-end module. The implemented simulator was validated using simulated data produced in MATLAB. The verification results confirmed that the simula...
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