- PAMI2024
- mmWave
- conference
- mmWave
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Clutter Suppression Techniques
Millimeter wave radar (mmWave radar) faces the challenge of high clutter from other electronic devices or objects in the environment, which can significantly degrade its performance. Beamforming, space-time coding, and multi-target tracking are three popular techniques used to suppress clutter in mmWave radar. Beamforming can adapt to changing environmental conditions and enhance range and accuracy. Space-time coding can handle complex environments with high clutter levels by exploiting the signal's spatial and temporal structure. Multi-target tracking combines information from multiple sensors to accurately track moving targets in a cluttered environment, using advanced techniques such as deep learning models.
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Cloud Profiling Radar
Cloud profiling radar, a type of Doppler radar, offers more accurate precipitation forecasts by providing detailed information about cloud formations and distributions. This technology is applied in various fields including agriculture, air traffic management, and environmental research. Its advantages over traditional methods include improved accuracy, real-time data generation, and flexibility.
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Chirp Signal Generation
Millimeter-wave radar (MWIR) is a radar technology operating in the 30 to 300 GHz frequency range. The chirp signal, used to modulate frequency, is generated digitally, with exponential and triangular shapes. MWIR radar's high frequency range enables long-distance detection through obstacles, rapid response time in emergency situations, improved S/N ratio, and various applications including air traffic control, border security, urban navigation, autonomous vehicles, search and rescue operations, fire detection, disaster relief, and military operations.
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Calibration of Signal Processing Algorithms
Calibration of signal processing algorithms is crucial for the accuracy and reliability of millimeter-wave radar (MWIR) systems. The process involves adjusting physical parameters to match the system's characteristics, accounting for environmental conditions, target movement, and interference sources. Techniques such as physical parameter estimation, statistical methods, machine learning, and real-time measurements can be used for calibration. By properly calibrating MWIR systems, applications in remote sensing, traffic management, and security surveillance can achieve better results.
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Calibration of Radar Antennas
Calibration of Radar Antennas is a crucial process that ensures accurate and reliable measurements of distance, speed, and direction. The accuracy of radar measurements depends heavily on the calibration of these antennas. There are several methods for calibration, including manual, automatic, laser, and image-based techniques. Radar antenna calibration has numerous applications in various industries such as transportation, security, disaster response, agriculture, etc. By understanding the importance of calibration and selecting the appropriate method for your needs, you can ensure optimal performance and safety in various industries.