Auswahl der wissenschaftlichen Literatur zum Thema „RADAR recognition process“
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Zeitschriftenartikel zum Thema "RADAR recognition process"
Dudczyk, Janusz, und Łukasz Rybak. „Application of Data Particle Geometrical Divide Algorithms in the Process of Radar Signal Recognition“. Sensors 23, Nr. 19 (30.09.2023): 8183. http://dx.doi.org/10.3390/s23198183.
Der volle Inhalt der QuelleXing, Huaixi, Qinghua Xing und Kun Wang. „Radar Anti-Jamming Countermeasures Intelligent Decision-Making: A Partially Observable Markov Decision Process Approach“. Aerospace 10, Nr. 3 (27.02.2023): 236. http://dx.doi.org/10.3390/aerospace10030236.
Der volle Inhalt der QuelleSun, Jingming, Qiang Zhang, Jingbei Yang und Yuhao Yang. „Automatic Sample Labeling Method for Radar Target Recognition“. Journal of Physics: Conference Series 2356, Nr. 1 (01.10.2022): 012029. http://dx.doi.org/10.1088/1742-6596/2356/1/012029.
Der volle Inhalt der QuelleBartsch, A., F. Fitzek und R. H. Rasshofer. „Pedestrian recognition using automotive radar sensors“. Advances in Radio Science 10 (18.09.2012): 45–55. http://dx.doi.org/10.5194/ars-10-45-2012.
Der volle Inhalt der QuelleVinogradova, N. S., und L. G. Dorosinsky. „Recognition of radar images generated by synthetic aperture radar systems“. Ural Radio Engineering Journal 5, Nr. 3 (2021): 258–71. http://dx.doi.org/10.15826/urej.2021.5.3.004.
Der volle Inhalt der QuelleLee, Gawon, und 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, Nr. 4 (18.02.2022): 2168. http://dx.doi.org/10.3390/app12042168.
Der volle Inhalt der QuelleDong, Xiaoxuan, und Siyi Cheng. „Radar Working Modes Recognition Based on Discrete Process Neural Network“. IOP Conference Series: Materials Science and Engineering 394 (08.08.2018): 042088. http://dx.doi.org/10.1088/1757-899x/394/4/042088.
Der volle Inhalt der QuelleYang, Rui, Yingbo Zhao und Yuan Shi. „RPREC: A Radar Plot Recognition Algorithm Based on Adaptive Evidence Classification“. Applied Sciences 13, Nr. 22 (20.11.2023): 12511. http://dx.doi.org/10.3390/app132212511.
Der volle Inhalt der QuelleFeng, Xiang, Zhengliang Shan, Zhanfeng Zhao, Zirui Xu, Tianpeng Zhang, Zihe Zhou, Bo Deng und Zirui Guan. „Millimeter-Wave Radar Monitoring for Elder’s Fall Based on Multi-View Parameter Fusion Estimation and Recognition“. Remote Sensing 15, Nr. 8 (16.04.2023): 2101. http://dx.doi.org/10.3390/rs15082101.
Der volle Inhalt der QuelleZhyrnov, V., und S. Solonska. „Intelligent model of radar object images for surveillance radars“. Radiotekhnika, Nr. 212 (28.03.2023): 148–54. http://dx.doi.org/10.30837/rt.2023.1.212.14.
Der volle Inhalt der QuelleDissertationen zum Thema "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.
Der volle Inhalt der QuelleMilitary 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.
Der volle Inhalt der QuelleMenon, 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.
Der volle Inhalt der QuelleBuchteile zum Thema "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.
Der volle Inhalt der QuelleEstrada, Jheanel, Gil Opina Jr und 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.
Der volle Inhalt der QuellePeralta, 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.
Der volle Inhalt der QuelleZhang, Suyu, Wenlong Zhao, Liang Guo, Ruijun Liu und Jun Liu. „Autonomous Driving System for Mining UGVs“. In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231117.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "RADAR recognition process"
Dankert, Heiko, Jochen Horstmann und 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.
Der volle Inhalt der QuelleMattei, 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.
Der volle Inhalt der QuelleJinzhu Wang, Jinzhu Wang, Jie Bai Jie Bai, Libo Huang Libo Huang und 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.
Der volle Inhalt der QuelleKhadr, N., D. O. Pederson, G. J. Salamo und 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.
Der volle Inhalt der QuelleKonopko, Mariola, und 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.
Der volle Inhalt der QuelleBacsardi, Laszlo, und 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.
Der volle Inhalt der QuelleLi, Yixiao, Yutaka Matsubara, Daniel Olbrys, Kazuhiro Kajio, Takashi Inada und 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.
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