Doppler radarsensor 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...
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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-b...
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The cooperative operation of roadside millimeter-wave (MMW) radarsensors can effectively extend the detection range of a single unit through data splicing. However, accurate calibration of their positions is required...
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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 processi...
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Monitoring construction sites through sensortechnology 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 i...
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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 naviga...
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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 radarsensor 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%.
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 angl...
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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 met...
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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, inc...
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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 demon...
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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.
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