Relevant bibliographies by topics / Multistatic ISAR

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Multistatic ISAR'

Author: Grafiati
Published: 29 March 2025

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Journal articles on the topic "Multistatic ISAR"

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Tang, Zheng-Zhao, Yang-Yang Dong, Chun-Xi Dong, Xin Chang, and Guo-Qing Zhao. "A Deception Jamming Method Countering Bi- and Multistatic ISAR Based on Micro-Doppler Effect." Mathematical Problems in Engineering 2018 (September 18, 2018): 1–6. http://dx.doi.org/10.1155/2018/3689382.

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Bi- and multistatic inverse synthetic aperture radar (ISAR) operate with spatially separated transmitting and receiving antennas. A deception jamming method countering bi- and multistatic ISAR is proposed in this paper based on the study of micro-Doppler effect. The jammer modulates the intercepted ISAR signals with added micro-Doppler information and retransmits them to the real target, which scatters the jamming signals to the radar receivers. Deceptive false-target images with interference bands in the cross-range direction will be induced by the jamming signals through the imaging process of radar receivers. Additionally, real-time movement features of the false-targets can be flexibly adjusted by changing the modulation parameters, which improves the fidelity of the false-targets. The equivalent number of looks (ENL) index is used to evaluate the jamming effects. Simulation results validate our theoretical analysis and show the effectiveness and practicability of our method.
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Brisken, Stefan, Dietmar Matthes, Torsten Mathy, and Josef Worms. "Spatially Diverse ISAR Imaging for Classification Performance Enhancement." International Journal of Electronics and Telecommunications 57, no. 1 (March 1, 2011): 15–21. http://dx.doi.org/10.2478/v10177-011-0002-2.

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Spatially Diverse ISAR Imaging for Classification Performance Enhancement One popular approach to the problem of Non-Cooperative Target Identification is the use of 2D Inverse SAR images. Methods to successfully identify a target include the comparison of a set of scattering centers in the ISAR image to a database or the estimation of target dimensions. While working well in theory, these techniques face major difficulties in practice. In the conventional case of a monostatic radar, visibility of scattering centers varies with the target aspect angle due to fading. In this paper we examine that the visibility of scattering centers can be improved by incoherent addition of images from spatially distributed radars. The main focus lies in the description and results of a multistatic ISAR experiment carried out at Fraunhofer FHR. We display theoretically derived bistatic synchronization errors in a practical system and formulate additional multistatic synchronization requirements, necessary to add up the images.
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Phan, An, Stefan Brisken, Brian W. ‐H Ng, and Hai‐Tan Tran. "Total rotational velocity estimation in a multistatic ISAR system." IET Radar, Sonar & Navigation 13, no. 3 (March 2019): 368–75. http://dx.doi.org/10.1049/iet-rsn.2018.5135.

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Brisken, Stefan, Marco Martorella, Torsten Mathy, Christoph Wasserzier, Josef G. Worms, and Joachim H. G. Ender. "Motion estimation and imaging with a multistatic ISAR system." IEEE Transactions on Aerospace and Electronic Systems 50, no. 3 (July 2014): 1701–14. http://dx.doi.org/10.1109/taes.2014.130099.

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Brisken, Stefan, and Marco Martella. "Multistatic ISAR autofocus with an image entropy-based technique." IEEE Aerospace and Electronic Systems Magazine 29, no. 7 (July 2014): 30–36. http://dx.doi.org/10.1109/maes.2014.130140.

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Pastina, Debora, Marta Bucciarelli, and Pierfrancesco Lombardo. "Multistatic and MIMO Distributed ISAR for Enhanced Cross-Range Resolution of Rotating Targets." IEEE Transactions on Geoscience and Remote Sensing 48, no. 8 (August 2010): 3300–3317. http://dx.doi.org/10.1109/tgrs.2010.2043740.

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Li, Ruize, Shuanghui Zhang, Chi Zhang, Yongxiang Liu, and Xiang Li. "A Multistatic ISAR Imaging Method Based on Similarity Prior With Overlaps Among Observation Angles." IEEE Geoscience and Remote Sensing Letters 20 (2023): 1–5. http://dx.doi.org/10.1109/lgrs.2023.3321718.

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Li, Ning, Ling Wang, and Gong Zhang. "High-resolution Side-view and Top-view Imaging Method of Ship Targets Using Multistatic ISAR." JOURNAL OF RADARS 1, no. 2 (August 2, 2012): 163–70. http://dx.doi.org/10.3724/sp.j.1300.2012.20021.

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Testa, Alejandro, Debora Pastina, and Fabrizio Santi. "Decentralized Approach for Translational Motion Estimation with Multistatic Inverse Synthetic Aperture Radar Systems." Remote Sensing 15, no. 18 (September 5, 2023): 4372. http://dx.doi.org/10.3390/rs15184372.

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This paper addresses the estimation of the target translational motion by using a multistatic Inverse Synthetic Aperture Radar (ISAR) system composed of an active radar sensor and multiple receiving-only devices. Particularly, a two-step decentralized technique is derived: the first step estimates specific signal parameters (i.e., Doppler frequency and Doppler rate) at the single-sensor level, while the second step exploits these estimated parameters to derive the target velocity and acceleration components. Specifically, the second step is organized in two stages: the former is for velocity estimation, while the latter is devoted to velocity estimation refinement if a constant velocity model motion can be regarded as acceptable, or to acceleration estimation if a constant velocity assumption does not apply. A proper decision criterion to select between the two motion models is also provided. A closed-form theoretical performance analysis is provided for the overall technique, which is then used to assess the achievable performance under different distributions of the radar sensors. Additionally, a comparison with a state-of-the-art centralized approach has been carried out considering computational burden and robustness. Finally, results obtained against experimental multisensory data are shown confirming the effectiveness of the proposed technique and supporting its practical application.
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Suwa, Kei, Toshio Wakayama, and Masafumi Iwamoto. "Three-Dimensional Target Geometry and Target Motion Estimation Method Using Multistatic ISAR Movies and Its Performance." IEEE Transactions on Geoscience and Remote Sensing 49, no. 6 (June 2011): 2361–73. http://dx.doi.org/10.1109/tgrs.2010.2095423.

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Dissertations / Theses on the topic "Multistatic ISAR"

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Yousfi, Fayin. "Multistatic ISAR imaging : image formation, structure analysis and motion estimation." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG014.

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L'imagerie ISAR (Inverse Synthetic Aperture Radar) monostatique fournit des images haute résolution d'objets en utilisant leur mouvement relatif par rapport à un radar. Ces images peuvent être utilisées pour des tâches d'identification et de classification. L'ajout de récepteurs bistatiques distants peut compléter l'imagerie monostatique en fournissant des géométries d'observation différentes. Cette thèse utilise la diversité d'images fournie par des configuration ISAR multistatiques dans le but d'obtenir des informations sur la structure et le mouvement de rotation d'avions et de satellites. Plus précisément, la diversité d'images peut être utilisée pour identifier des éléments non isotropes qui ne sont visibles que sous certains angles, et donc uniquement sur certaines images. D'autres éléments sont visibles sur de multiples images. En mettant en correspondance leurs projections sur les différentes images, le mouvement de rotation de l'objet ainsi que les coordonnées de ces éléments peuvent être estimés. Pour atteindre ces objectifs, un formalisme utilisant des bases orthogonales est développé pour définir précisément le mouvement 3D d'un objet et les projections ISAR fournies par les différents observateurs. Sur la base de ce formalisme, deux méthodes d'estimation 3D sont développées. La première fait correspondre des zones planes d'un objet stabilisé pour estimer leur normale. La seconde estime les coordonnées d'éléments linéaires d'un objet en faisant correspondre leurs projections dans les images ISAR. Cette méthode permet également l'estimation du spin de l'objet. Des formules d'incertitude sont calculées pour évaluer la précision de ces estimations. Les deux méthodes sont validées avec des données réelles de satellites et d'avions. Les données sur avions ont été recueillies lors d'essais bistatiques menés près de l'aéroport d'Orly, tandis que les données sur satellites ont été acquises lors d'essais bistatiques à longue distance entre la France et l'Allemagne. Pour générer des images à partir des données numérisées, un traitement ISAR robuste, adapté à la géométrie bistatique et au faible SNR est développé. Les images d'avions ont permis de déterminer l'attitude complète d'un avion. Les images satellites ont été utilisées pour estimer la longueur et l'orientation relative des différents éléments des satellites SWARM-B, Kosmos 1300 et ENVISAT, ainsi que pour déterminer le vecteur de rotation d'ENVISAT
Monostatic ISAR (Inverse Synthetic Aperture Radar) imaging provides high-resolution images of object based on their relative motion to a radar. These images can be used for identification and classifications tasks. The addition of distant bistatic receivers can complement monostatic imaging by providing different observation geometries. This PhD aims at deriving information on the structure and the rotational motion of aircraft and satellites using multiple ISAR observers. More specifically, the difference between ISAR images can be used to identify non-isotropic features, such as solar panels, that are only visible through specific aspect angles. Furthermore, other features visible on multiple images can be exploited to estimate the rotational motion of the imaged object and to retrieve 3-Dimensional information. To meet these objectives, a formalism based on frames is developed to define accurately 3D motions and the ISAR projections provided by the different observers. Based on this formalism, two methods for 3D estimation are developed. The first method matches flat areas of a stabilized object to estimate their normal. The second method estimates the coordinates of linear features of an object by matching their projections in the ISAR images. This method also enables the estimation of the spin of the object. Uncertainty formulas are derived to assess the accuracy of these estimations. Both methods are validated with real satellite and aircraft data. The aircraft data were gathered during bistatic trials conducted near Orly airport, while the satellite data were collected during long-baseline bistatic trials between France and Germany. To generate images from the recorded data, a robust ISAR processing adapted to the bistatic geometry and to low SNR data is developed. With the aircraft images, the complete attitude of an aircraft is estimated. With the satellite images, the length and relative orientation of features of the satellites SWARM-B, Kosmos 1300 and ENVISAT as well as the spin of ENVISAT are estimated
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Book chapters on the topic "Multistatic ISAR"

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Bączyk, Marcin Kamil. "Passive multistatic ISAR imaging." In Multidimensional Radar Imaging. Volume 2, 127–57. United Kingdom: SciTech Publishing Inc., 2024. https://doi.org/10.1049/sbra562e_ch6.

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"Sparsity-driven multistatic ISAR image reconstruction." In Multidimensional Radar Imaging, 235–51. Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/sbra527e_ch7.

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"Multistatic 3D ISAR imaging of maritime targets." In Multidimensional Radar Imaging, 287–309. Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/sbra527e_ch9.

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Conference papers on the topic "Multistatic ISAR"

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Gröneweg, Jan-Steffen, Soheil Gherekhloo, Maximilian Lübke, and Norman Franchi. "Evaluating the Performance of UE-Side Sensing in Multistatic ISAC Systems for Highway Scenarios." In 2025 IEEE 5th International Symposium on Joint Communications & Sensing (JC&S), 1–6. IEEE, 2025. https://doi.org/10.1109/jcs64661.2025.10880653.

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Zhuge, Shun, Yugang Ma, Zhiping Lin, and Yonghong Zeng. "A Novel Geometric Solution for Moving Target Localization Through Multistatic Sensing in the ISAC System." In 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), 1–5. IEEE, 2024. http://dx.doi.org/10.1109/vtc2024-spring62846.2024.10683032.

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van Dorp, P., J. M. M. Verzeilberg, and M. P. G. Otten. "Coherent multistatic ISAR imaging." In IET International Conference on Radar Systems (Radar 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.1624.

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Brisken, Stefan. "Multistatic ISAR - chances and challenges." In 2014 International Radar Conference (Radar). IEEE, 2014. http://dx.doi.org/10.1109/radar.2014.7060243.

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Salvetti, Federica, Daniele Stagliano, Elisa Giusti, and Marco Martorella. "Multistatic 3D ISAR image reconstruction." In 2015 IEEE International Radar Conference (RadarCon). IEEE, 2015. http://dx.doi.org/10.1109/radar.2015.7131075.

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Brisken, S., T. Mathy, E. Giusti, M. Martorella, and C. Wasserzier. "Multistatic ISAR autofocussing using image contrast optimization." In IET International Conference on Radar Systems (Radar 2012). Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.1623.

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Testa, Alejandro, Fabrizio Santi, and Debora Pastina. "Translational motion estimation with multistatic ISAR systems." In 2021 International Radar Symposium (IRS). IEEE, 2021. http://dx.doi.org/10.23919/irs51887.2021.9466180.

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Nassib, Ali, Tadahiro Negishi, Danilo Erricolo, Michael C. Wicks, and Lorenzo Lo Monte. "A dyadic target model for multistatic SAR/ISAR imaging." In 2015 IEEE International Radar Conference (RadarCon). IEEE, 2015. http://dx.doi.org/10.1109/radar.2015.7131235.

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Turin, Fabrizio, and Debora Pastina. "Multistatic passive ISAR based on geostationary satellites for coastal surveillance." In 2013 IEEE Radar Conference (RadarCon). IEEE, 2013. http://dx.doi.org/10.1109/radar.2013.6586123.

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Rattan, A., D. Andre, and M. Finnis. "Multistatic hybrid SAR/ISAR data generation using a stationary target." In International Conference on Radar Systems (RADAR 2022). Institution of Engineering and Technology, 2022. http://dx.doi.org/10.1049/icp.2022.2294.

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