Academic literature on the topic 'ISAR'

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Journal articles on the topic "ISAR"

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Matthews, Thomas J., François Rigal, Kostas A. Triantis, and Robert J. Whittaker. "A global model of island species–area relationships." Proceedings of the National Academy of Sciences 116, no. 25 (2019): 12337–42. http://dx.doi.org/10.1073/pnas.1818190116.

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The increase in species richness with island area (ISAR) is a well-established global pattern, commonly described by the power model, the parameters of which are hypothesized to vary with system isolation and to be indicative of ecological process regimes. We tested a structural equation model of ISAR parameter variation as a function of taxon, isolation, and archipelago configuration, using a globally distributed dataset of 151 ISARs encompassing a range of taxa and archipelago types. The resulting models revealed a negative relationship between ISAR intercept and slope as a function of archi
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Sommers, Pacifica, Dorota L. Porazinska, John L. Darcy, et al. "Microbial Species–Area Relationships in Antarctic Cryoconite Holes Depend on Productivity." Microorganisms 8, no. 11 (2020): 1747. http://dx.doi.org/10.3390/microorganisms8111747.

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The island species–area relationship (ISAR) is a positive association between the number of species and the area of an isolated, island-like habitat. ISARs are ubiquitous across domains of life, yet the processes generating ISARs remain poorly understood, particularly for microbes. Larger and more productive islands are hypothesized to have more species because they support larger populations of each species and thus reduce the probability of stochastic extinctions in small population sizes. Here, we disentangled the effects of “island” size and productivity on the ISAR of Antarctic cryoconite
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Schulz, Stefanie, Julinda Mehilli, Albert Schömig, and Adnan Kastrati. "ISAR." Circulation Journal 74, no. 9 (2010): 1771–78. http://dx.doi.org/10.1253/circj.cj-10-0738.

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Zhu, Xinli, Yasheng Zhang, Wang Lu, Yuqiang Fang, and Jun He. "An ISAR Image Component Recognition Method Based on Semantic Segmentation and Mask Matching." Sensors 23, no. 18 (2023): 7955. http://dx.doi.org/10.3390/s23187955.

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The inverse synthetic aperture radar (ISAR) image is a kind of target feature data acquired by radar for moving targets, which can reflect the shape, structure, and motion information of the target, and has attracted a great deal of attention from the radar automatic target recognition (RATR) community. The identification of ISAR image components in radar satellite identification missions has not been carried out in related research, and the relevant segmentation methods of optical images applied to the research of semantic segmentation of ISAR images do not achieve ideal segmentation results.
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Feng, Tiantian, and Lixin Guo. "Multiview ISAR Imaging for Complex Targets Based on Improved SBR Scattering Model." International Journal of Antennas and Propagation 2021 (January 25, 2021): 1–10. http://dx.doi.org/10.1155/2021/6615154.

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A novel multiview inverse synthetic aperture radar (ISAR) imaging method is proposed to simulate high-resolution and identifiable ISAR image of complex targets by handling large-angle and wide-bandwidth scattering data. The scattering data are simulated with the shooting and bouncing ray (SBR) method. The bidirectional ray-tracing algorithm is developed to reduce the computation time. Simulation results indicate that the improved method is efficient and reliable to calculate electromagnetic (EM) scattering of electrically large targets. To implement the multiview ISAR imaging method after data
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Ni, Peishuang, Yanyang Liu, Hao Pei, Haoze Du, Haolin Li, and Gang Xu. "CLISAR-Net: A Deformation-Robust ISAR Image Classification Network Using Contrastive Learning." Remote Sensing 15, no. 1 (2022): 33. http://dx.doi.org/10.3390/rs15010033.

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The inherent unknown deformations of inverse synthetic aperture radar (ISAR) images, such as translation, scaling, and rotation, pose great challenges to space target classification. To achieve high-precision classification for ISAR images, a deformation-robust ISAR image classification network using contrastive learning (CL), i.e., CLISAR-Net, is proposed for deformation ISAR image classification. Unlike traditional supervised learning methods, CLISAR-Net develops a new unsupervised pretraining phase, which means that the method uses a two-phase training strategy to achieve classification. In
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Deng, Jie, and Fulin Su. "SDRnet: A Deep Fusion Network for ISAR Ship Target Recognition Based on Feature Separation and Weighted Decision." Remote Sensing 16, no. 11 (2024): 1920. http://dx.doi.org/10.3390/rs16111920.

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Existing methods for inverse synthetic aperture radar (ISAR) target recognition typically rely on a single high-resolution radar signal type, such as ISAR images or high-resolution range profiles (HRRPs). However, ISAR images and HRRP data offer representations of targets across different aspects, each containing valuable information crucial for radar target recognition. Moreover, the process of generating ISAR images inherently facilitates the acquisition of HRRP data, ensuring timely data collection. Therefore, to fully leverage the different information from both HRRP data and ISAR images a
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Jin, Xinfei, Hongxu Li, Xinbo Xu, Zihan Xu, and Fulin Su. "Inverse Synthetic Aperture Radar Image Multi-Modal Zero-Shot Learning Based on the Scattering Center Model and Neighbor-Adapted Locally Linear Embedding." Remote Sensing 17, no. 4 (2025): 725. https://doi.org/10.3390/rs17040725.

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Inverse Synthetic Aperture Radar (ISAR) images are extensively used in Radar Automatic Target Recognition (RATR) for non-cooperative targets. However, acquiring training samples for all target categories is challenging. Recognizing target classes without training samples is called Zero-Shot Learning (ZSL). When ZSL involves multiple modalities, it becomes Multi-modal Zero-Shot Learning (MZSL). To achieve MZSL, a framework is proposed for generating ISAR images with optical image aiding. The process begins by extracting edges from optical images to capture the structure of ship targets. These e
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Mirajkar, Richa, Aditi Hulaji, Komal Sutar, et al. "Evolutionary Developments in 3D ISAR Imaging: From Early Techniques to Modern Solution." Journal of VLSI Design and Signal Processing 10, no. 3 (2024): 32–61. https://doi.org/10.46610/jovdsp.2024.v10i03.004.

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This review paper delves into the advancements in 3D ISAR imaging technology, focusing on the progression from traditional two-dimensional (2D) ISAR techniques to contemporary 3D approaches. ISAR imaging is pivotal in military and civilian radar applications, providing high-resolution images for moving targets. At the same time, 2D ISAR imaging techniques have been instrumental in target detection and tracking, but they are limited in reconstructing complex geometrical details of targets. 3D ISAR overcomes this limitation by incorporating multiple views or sensors to provide a three-dimensiona
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Jiang, Shengteng, Xiaoyuan Ren, Canyu Wang, Libing Jiang, and Zhuang Wang. "A Self-Supervised Feature Point Detection Method for ISAR Images of Space Targets." Remote Sensing 17, no. 3 (2025): 441. https://doi.org/10.3390/rs17030441.

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Feature point detection in inverse synthetic aperture radar (ISAR) images of space targets is the foundation for tasks such as analyzing space target motion intent and predicting on-orbit status. Traditional feature point detection methods perform poorly when confronted with the low texture and uneven brightness characteristics of ISAR images. Due to the nonlinear mapping capabilities, neural networks can effectively learn features from ISAR images of space targets, providing new ideas for feature point detection. However, the scarcity of labeled ISAR image data for space targets presents a ch
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Dissertations / Theses on the topic "ISAR"

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Kucukkilic, Talip. "Isar Imaging And Motion Compensation." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12608102/index.pdf.

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In Inverse Synthetic Aperture Radar (ISAR) systems the motion of the target can be classified in two main categories: Translational Motion and Rotational Motion. A small degree of rotational motion is required in order to generate the synthetic aperture of the ISAR systems. On the other hand, the remaining part of the target&rsquo<br>s motion, that is any degree of translational motion and the large degree of rotational motion, degrades ISAR image quality. Motion compensation techniques focus on eliminating the effect of the targets&rsquo<br>motion on the ISAR images. In this thesis, ISAR im
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Atilgan, Erdinc Levent. "Target Identification Using Isar Imaging Techniques." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606765/index.pdf.

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A proper time-frequency transform technique suppresses the blurring and smearing effect of the time-varying Doppler shift on the target image. The conventional target imaging method uses the Fourier transform for extracting the Doppler shift from the received radar pulse. Since the Doppler shift is timevarying for rotating targets, the constructed images will be degraded. In this thesis, the Doppler shift information required for the Range-Doppler image of the target is extracted by using high resolution time-frequency transform techniques. The Wigner-Ville Distribution and the Adaptive Gabor
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Tufan, Alper. "Comparative Evaluation Of Isar Processing Algorithms." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614709/index.pdf.

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In this thesis, Inverse Synthtetic Aperture Radar image reconstruction techniques, named as Range Doppler, Back Projection, Polar Formatting, Multiple Signal Classification (MUSIC) and Time Frequency techniques are analysed and compared using simulations. Time Frequency techniques investigated in this thesis are Short Time Fourier Transform, Wigner-Ville Distribution, Smoothed Wigner-Ville Distribution and Choi-Williams Distribution. First, some fundamental concepts of ISAR, such as resolution, range profile, time dependent Doppler frequency are given. A data simulator is designed and implemen
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Forrester, Neil T. "Surface reconstruction from interferometric ISAR data." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/91809.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February 2014.<br>Cataloged from PDF version of thesis. "November, 2013."<br>Includes bibliographical references (pages [137]-139).<br>A frequently useful technique in the interpretation of Inverse Synthetic Aperture Radar (ISAR) images is to construct a three dimensional (3D) model of the object being imaged. Generally, such models are constructed manually by an analyst based on a series of radar images and whatever other information is available. However, using multistatic radar
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Nassib, Ali Hussein. "Isar Target Reconstruction Via Dipole Modeling." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1461250663.

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Lucrecio, Armando. "ISAR imaging using Fourier and wavelet transforms." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion-image.exe/07Dec%5FLucrecio.pdf.

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Thesis (M.S. in Physics)--Naval Postgraduate School, December 2007.<br>Thesis Advisor(s): Borden, Brett ; Cristi, Roberto. "December 2007." Description based on title screen as viewed on January 23, 2008 Includes bibliographical references (p. 61-62). Also available in print.
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Martin, Jennifer. "Imagerie Isar à l'aide de l'algorithme génétique." Thesis, Université Laval, 2010. http://www.theses.ulaval.ca/2010/27630/27630.pdf.

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Bill, Hans-Christoph. "Besiedlungsdynamik und Populationsbiologie charakteristischer Pionierpflanzenarten nordalpiner Wildflüsse /." Marburg : Görich & Weiershäuser, 2000. http://www.gbv.de/dms/bs/toc/319626016.pdf.

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Logoglu, Berker. "Performance Of Bilinear Time-frequency Transforms In Isar." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12609166/index.pdf.

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In this thesis a stepped-frequency Inverse Synthetic Aperture Radar (ISAR) is employed to develop two-dimensional range-Doppler images of a small ghter aircraft which exhibits three dimensional rotational rotation. The simulation is designed such that the target can exhibit yaw, pitch and roll motions at the same time. First, radar returns from prominent scatterers of various parts of the target are processed and displayed using conventional Fourier transform. The eects of dierent complex motion types and scenarios are observed and discussed. Then, several linear and bi-linear time-frequency d
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Lim, Kian Guan. "Battle damage assessment using inverse synthetic aperture radar (ISAR)." Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1223.

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Approved for public release; distribution in unlimited.<br>An imaging radar, like ISAR, offers a combatant the capability to perform long range surveillance with high quality imagery for positive target identification. Extending this attractive feature to the battle damage assessment problem (BDA) gives the operator instant viewing of the target's behavior when it is hit. As a consequence, immediate and decisive action can be quickly taken (if required). However, the conventional Fourier processing adopted by most ISAR systems does not provide adequate time resolution to capture the target's d
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Books on the topic "ISAR"

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Porter, Nicholas John. A generalised theory of SAR, ISAR and hybrid SAR/ISAR imaging. University of Birmingham, 1996.

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Rädlinger, Christine. Geschichte der Isar in München. Stadtarchiv München, 2012.

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Ertle, Uli. Die Isar: Stadt, Mensch, Fluss. 2nd ed. Süddeutsche Zeitung GmbH, 2011.

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Sokolovska, Viktorija. Isar-Marvinci i Povardarjeto vo antičko vreme =: Isar-Marvinci and the Vardar Valley in ancient times. Muzej na Makedonija, 1986.

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Sokolovska, Viktorija. Isar--Marvinci i Povardarjeto vo antičko vreme. Muzej na Makedonija, 1986.

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Gerhard, Hackl, ed. Das bayerische Oberland zwischen Isar und Inn. Rosenheimer Verlagshaus, 1987.

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Greindl, Gabriele. Niederbayern, Oberpfalz: Kunstfahrten zwischen Isar und Naab. Süddeutscher Verlag, 1990.

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Veronika, Werner, ed. Das bayerische Oberland zwischen Isar und Lech. Rosenheimer Verlagshaus, 1986.

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Riffler, Bernd. Radeln im Sudosten Munchens: Zwischen Isar und Inn. Suddeutscher Verlag, 1986.

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Kong, Kim Kok. Focusing of inverse synthetic aperture radar (ISAR) images. University of Birmingham, 1995.

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Book chapters on the topic "ISAR"

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Wenzel, Markus, and Larry Paulson. "Isabelle/Isar." In The Seventeen Provers of the World. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11542384_8.

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Meurer, Rolf. "Kraftwerkstreppe Mittlere Isar." In Wasserbau und Wasserwirtschaft in Deutschland. Vieweg+Teubner Verlag, 2000. http://dx.doi.org/10.1007/978-3-322-80213-2_45.

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Bączyk, Marcin Kamil. "Passive multistatic ISAR imaging." In Multidimensional Radar Imaging. Volume 2. SciTech Publishing Inc., 2024. https://doi.org/10.1049/sbra562e_ch6.

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Qian, Yu, and Tao Hong. "2D ISAR Imaging Using SFFT." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8944-2_74.

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Nipkow, Tobias. "Structured Proofs in Isar/HOL." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-39185-1_15.

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Pai, Jeffrey S. C., Wolfgang Polasek, and Hideo Kozumi. "Irregularly Spaced AR (ISAR) Models." In Studies in Classification, Data Analysis, and Knowledge Organization. Springer Japan, 1998. http://dx.doi.org/10.1007/978-4-431-65950-1_27.

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Jun, Wang, and Wan Dongdong. "Ship Target Segmentation in ISAR Images." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34531-9_64.

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Haftmann, Florian, and Makarius Wenzel. "Local Theory Specifications in Isabelle/Isar." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02444-3_10.

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Nipkow, Tobias, and Gerwin Klein. "Isar: a Language for Structured Proofs." In Concrete Semantics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10542-0_5.

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Wenzel, Makarius. "Structured Induction Proofs in Isabelle/Isar." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11812289_3.

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Conference papers on the topic "ISAR"

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Gui, Shuliang, Haibo Peng, Yuan Xu, Zhiqin Zhao, Luhong Fan, and Zengshan Tian. "An ISAC-ISAR Imaging and Tracking Method for Moving Target Sensing." In 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2024. https://doi.org/10.1109/icsidp62679.2024.10869222.

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Özdemir, Caner. "Review of Inverse Synthetic Aperture Radar (ISAR), Polarimetric ISAR Imaging and Interpretation." In 2023 20th International Bhurban Conference on Applied Sciences and Technology (IBCAST). IEEE, 2023. http://dx.doi.org/10.1109/ibcast59916.2023.10712932.

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Wang, Yue, and Xueru Bai. "ISAR-Diff: A High-Resolution ISAR Imaging Method Based on Conditional Diffusion Models." In 2024 IEEE International Conference on Signal, Information and Data Processing (ICSIDP). IEEE, 2024. https://doi.org/10.1109/icsidp62679.2024.10869095.

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Tang, Min, Jiang Qian, Haitao Lyu, and Jiayang Wu. "ISAR Imaging with Envelope Information." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642590.

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Giusti, Elisa, Selenia Ghio, Marco Martorella, Luca Banchi, and Federico Principi. "Ship-borne 3D ISAR Imaging." In 2024 International Radar Conference (RADAR). IEEE, 2024. https://doi.org/10.1109/radar58436.2024.10993838.

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"SAR and ISAR." In 2017 IEEE Microwaves, Radar and Remote Sensing Symposium (MRRS). IEEE, 2017. http://dx.doi.org/10.1109/mrrs.2017.8075077.

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Aleksoff, Carl C., and Nikola S. Subotic. "Optoelectronic ISAR processing." In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, edited by William J. Miceli. SPIE, 1995. http://dx.doi.org/10.1117/12.216965.

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Pui, Chow Yii, Brian Ng, Luke Rosenberg, and Tri-Tan Cao. "Polarimetric 3D-ISAR." In 2022 IEEE Radar Conference (RadarConf22). IEEE, 2022. http://dx.doi.org/10.1109/radarconf2248738.2022.9764309.

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Chen, Victor C., and Baokun Liu. "Hybrid SAR/ISAR for distributed ISAR imaging of moving targets." In 2015 IEEE International Radar Conference (RadarCon). IEEE, 2015. http://dx.doi.org/10.1109/radar.2015.7131078.

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Song, Jung-Hwan, Woo-Kyung Lee, and Chul H. Jung. "High resolution ISAR processing using real data: ISAR-to-SAR approach." In 2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR). IEEE, 2015. http://dx.doi.org/10.1109/apsar.2015.7306266.

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Reports on the topic "ISAR"

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Chambers, David H. Polarimetric ISAR: Simulation and image reconstruction. Office of Scientific and Technical Information (OSTI), 2016. http://dx.doi.org/10.2172/1247281.

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Doerry, Armin Walter. Ship dynamics for maritime ISAR imaging. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/929523.

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Rihaczek, A. W., R. L. Mitchell, and S. J. Hershkowitz. Non-Cooperative Moving Target Recognition Using ISAR. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada399759.

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Goldman, Geoffrey H., and Herbert Dropkin. High-Frequency Autofocus Algorithm for Noncooperative ISAR. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada364068.

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Doerry, Armin Walter. Performance limits for maritime Inverse Synthetic Aperture Radar (ISAR). Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1121940.

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Mayhan, Joseph T. Phase-Enhanced" 3D Snapshot ISAR Imaging and Interferometric SAR". Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada511473.

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Madden, Richard. An Introduction to the Functionality of the ISAR Radar. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada389350.

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Gatesman, A. J., C. Beaudoin, R. H. Giles, et al. A Signature Correlation Study of Ground Target VHF/UHF ISAR Imagery. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada462278.

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Sorensen, K. W. Coherent change detection and interferometric ISAR measurements in the folded compact range. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/400087.

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Poirier, J. L., James Emstmeyer, Peter Franch, Chet Ouch, and John K. Schindler. UHF Strip - SAR and ISAR Images of a Tank: Application of Scale - Model Measurements. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada423762.

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