Literatura científica selecionada sobre o tema "RADAR recognition process"
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Artigos de revistas sobre o assunto "RADAR recognition process"
Dudczyk, Janusz, e Łukasz Rybak. "Application of Data Particle Geometrical Divide Algorithms in the Process of Radar Signal Recognition". Sensors 23, n.º 19 (30 de setembro de 2023): 8183. http://dx.doi.org/10.3390/s23198183.
Texto completo da fonteXing, Huaixi, Qinghua Xing e Kun Wang. "Radar Anti-Jamming Countermeasures Intelligent Decision-Making: A Partially Observable Markov Decision Process Approach". Aerospace 10, n.º 3 (27 de fevereiro de 2023): 236. http://dx.doi.org/10.3390/aerospace10030236.
Texto completo da fonteSun, Jingming, Qiang Zhang, Jingbei Yang e Yuhao Yang. "Automatic Sample Labeling Method for Radar Target Recognition". Journal of Physics: Conference Series 2356, n.º 1 (1 de outubro de 2022): 012029. http://dx.doi.org/10.1088/1742-6596/2356/1/012029.
Texto completo da fonteBartsch, A., F. Fitzek e R. H. Rasshofer. "Pedestrian recognition using automotive radar sensors". Advances in Radio Science 10 (18 de setembro de 2012): 45–55. http://dx.doi.org/10.5194/ars-10-45-2012.
Texto completo da fonteVinogradova, N. S., e L. G. Dorosinsky. "Recognition of radar images generated by synthetic aperture radar systems". Ural Radio Engineering Journal 5, n.º 3 (2021): 258–71. http://dx.doi.org/10.15826/urej.2021.5.3.004.
Texto completo da fonteLee, Gawon, e Jihie Kim. "Improving Human Activity Recognition for Sparse Radar Point Clouds: A Graph Neural Network Model with Pre-Trained 3D Human-Joint Coordinates". Applied Sciences 12, n.º 4 (18 de fevereiro de 2022): 2168. http://dx.doi.org/10.3390/app12042168.
Texto completo da fonteDong, Xiaoxuan, e Siyi Cheng. "Radar Working Modes Recognition Based on Discrete Process Neural Network". IOP Conference Series: Materials Science and Engineering 394 (8 de agosto de 2018): 042088. http://dx.doi.org/10.1088/1757-899x/394/4/042088.
Texto completo da fonteYang, Rui, Yingbo Zhao e Yuan Shi. "RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification". Applied Sciences 13, n.º 22 (20 de novembro de 2023): 12511. http://dx.doi.org/10.3390/app132212511.
Texto completo da fonteFeng, Xiang, Zhengliang Shan, Zhanfeng Zhao, Zirui Xu, Tianpeng Zhang, Zihe Zhou, Bo Deng e Zirui Guan. "Millimeter-Wave Radar Monitoring for Elder’s Fall Based on Multi-View Parameter Fusion Estimation and Recognition". Remote Sensing 15, n.º 8 (16 de abril de 2023): 2101. http://dx.doi.org/10.3390/rs15082101.
Texto completo da fonteZhyrnov, V., e S. Solonska. "Intelligent model of radar object images for surveillance radars". Radiotekhnika, n.º 212 (28 de março de 2023): 148–54. http://dx.doi.org/10.30837/rt.2023.1.212.14.
Texto completo da fonteTeses / dissertações sobre o assunto "RADAR recognition process"
Mottier, Manon. "Optimal Transport : an application to the RADAR Recognition Process for deinterleaving RADAR pulses and identifying emitter". Electronic Thesis or Diss., université Paris-Saclay, 2024. https://theses.hal.science/tel-04653381.
Texto completo da fonteMilitary intelligence is essential to a country's security and defense, particularly signals intelligence (ROEM). The emergence of passive systems has given a considerable advantage to those capable of controlling them by allowing discreet surveillance at a lower cost. However, the interception and processing of signals by a passive RADAR require establishing a dedicated algorithmic processing chain capable of understanding the diversity of electromagnetic spectra and the underlying physical phenomena. Over the years, the issues have become more complex and diversified, mainly because of numerous technological innovations that have led to the complexity and sophistication of electronic equipment; RADARs have more similar electromagnetic spectra, making their differentiation complex. This work proposes a RADAR Recognition Process first to deinterleave a signal and then to identify the RADARs. First, two new unsupervised deinterleaving approaches are proposed based on a combination of clustering algorithms integrating optimal transport distances to separate the pulses into several clusters before grouping the clusters belonging to the same RADAR. Finally, when the deinterleaving phase is completed, the RADARs are identified by developing an optimal transport distance between a reference database and the sets of previously deinterleaved pulses while modeling the phenomenon of missing pulses
Menon, K. Rajalakshmi. "Application Of High Frequency Natural Resonances Extracted From Electromagnetic Scattering Response For Discrimination Of Radar Targets With Minor Variations". Thesis, Indian Institute of Science, 2001. https://etd.iisc.ac.in/handle/2005/159.
Texto completo da fonteMenon, K. Rajalakshmi. "Application Of High Frequency Natural Resonances Extracted From Electromagnetic Scattering Response For Discrimination Of Radar Targets With Minor Variations". Thesis, Indian Institute of Science, 2001. http://hdl.handle.net/2005/159.
Texto completo da fonteCapítulos de livros sobre o assunto "RADAR recognition process"
Mahmoudi, Elham, Jan Düllmann, Lukas Heußner, Raoul Hölter, Andre Lamert, Shorash Miro, Thomas Möller et al. "Advance Reconnaissance and Optimal Monitoring". In Interaction Modeling in Mechanized Tunneling, 9–91. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-24066-9_2.
Texto completo da fonteEstrada, Jheanel, Gil Opina Jr e Anshuman Tripathi. "Object and Traffic Light Recognition Model Development Using Multi-GPU Architecture for Autonomous Bus". In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210286.
Texto completo da fontePeralta, Dan-el Padilla. "Pilgrimage to Mid-Republican Rome". In Divine Institutions, 178–229. Princeton University Press, 2020. http://dx.doi.org/10.23943/princeton/9780691168678.003.0005.
Texto completo da fonteZhang, Suyu, Wenlong Zhao, Liang Guo, Ruijun Liu e Jun Liu. "Autonomous Driving System for Mining UGVs". In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231117.
Texto completo da fonteTrabalhos de conferências sobre o assunto "RADAR recognition process"
Dankert, Heiko, Jochen Horstmann e Wolfgang Rosenthal. "Detection of Extreme Waves in SAR Images and Radar-Image Sequences". In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28160.
Texto completo da fonteMattei, F. "Enhanced radar detection of small remotely piloted aircraft in U-space scenario". In Aerospace Science and Engineering. Materials Research Forum LLC, 2023. http://dx.doi.org/10.21741/9781644902677-3.
Texto completo da fonteJinzhu Wang, Jinzhu Wang, Jie Bai Jie Bai, Libo Huang Libo Huang e Huanlei Chen Huanlei Chen. "Autonomous Driving Decision-making Based on the Combination of Deep Reinforcement Learning and Rule-based Controller". In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2021-acm-108.
Texto completo da fonteKhadr, N., D. O. Pederson, G. J. Salamo e B. A. Weber. "Symmetry perception by optical transformation". In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1987. http://dx.doi.org/10.1364/oam.1987.mm5.
Texto completo da fonteKonopko, Mariola, e Małgorzata Ewa Wysocka. "GPR Method as a Non-Invasive Method for Investigating Organic Soils Deposited under Designed Road Construction". In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.140.
Texto completo da fonteBacsardi, Laszlo, e Laszlo Csurgai Horvath. "Establishment of the Space Engineering Program in Hungary". In Symposium on Space Educational Activities (SSAE). Universitat Politècnica de Catalunya, 2022. http://dx.doi.org/10.5821/conference-9788419184405.068.
Texto completo da fonteLi, Yixiao, Yutaka Matsubara, Daniel Olbrys, Kazuhiro Kajio, Takashi Inada e Hiroaki Takada. "Agile Software Design Verification and Validation (V&V) for Automated Driving". In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-ves-017.
Texto completo da fonte