{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:53:14Z","timestamp":1760147594192,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,14]],"date-time":"2023-02-14T00:00:00Z","timestamp":1676332800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The use of satellite synthetic aperture radar (SAR) for moving target imaging has gained popularity recently. Researchers are focused on improving its imaging quality. To achieve high-quality and fast imaging, we have developed a dual-mode refocusing algorithm. We optimized the algorithm\u2019s target speed estimation and carried out data enhancement and quantization design for SAR image refocusing. The design is implemented on a Xilinx XC5VFX130T FPGA. The dual-mode image data are based on a slice size of 512 \u00d7 512 for slice mode and 256 \u00d7 256 for scan mode in a time-series function simulation. The serial\u2013parallel conversion and pipeline design balances the operating speed and logic resources for optimal performance. Experiment results on slice data of real SAR images show that the system\u2019s processing speed can reach two frames per second, utilizing 69633 LUTs, 255 RAMs, and 296 DSPs.<\/jats:p>","DOI":"10.3390\/s23042143","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T02:01:10Z","timestamp":1676426470000},"page":"2143","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hardware Accelerated Design of a Dual-Mode Refocusing Algorithm for SAR Imaging Systems"],"prefix":"10.3390","volume":"23","author":[{"given":"Le","family":"Yu","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China"},{"name":"China Light Industry Key Laboratory of Industrial Internet and Big Data, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaqi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2395-6593","authenticated-orcid":false,"given":"Nansong","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Engineering, Sonoma State University, Rohnert Park, CA 94928, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","article-title":"A tutorial on synthetic aperture radar","volume":"1","author":"Moreira","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1109\/TGRS.2019.2945875","article-title":"MEO SAR: System Concepts and Analysis","volume":"58","author":"Matar","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","unstructured":"Curlander, J.C., and McDonough, R. (1991). Synthetic Aperture Radar: Systems and Signal Processing, Wiley."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Liu, L., Zheng, P., Xu, P., Zhang, T., and Liu, S. (2021, January 19\u201321). A spaceborne multi-channel SAR imaging algorithm for moving Targets. Proceedings of the 2021 6th International Conference on Communication, Image and Signal Processing (CCISP), Chengdu, China.","DOI":"10.1109\/CCISP52774.2021.9639322"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Rui, G., Zhao, Z., Rui, G., Guobin, J., Mengdao, X., and Yongfeng, Z. (2021, January 3\u20135). Ocean Target Investigation Using Spaceborne SAR under Dual-Polarization Strip-map Mode. Proceedings of the 2021 2nd China International SAR Symposium (CISS), Shanghai, China.","DOI":"10.23919\/CISS51089.2021.9652375"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1109\/TAES.1971.310292","article-title":"Synthetic Aperture Imaging Radar and Moving Targets","volume":"3","author":"Raney","year":"1971","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1109\/TAES.2007.4383594","article-title":"Improved global range alignment for ISAR","volume":"43","author":"Wang","year":"2007","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_8","first-page":"600","article-title":"An Improved Phase Gradient Autofocus Algorithm Used in Real-time Processing","volume":"4","year":"2015","journal-title":"J. Radars"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"468","DOI":"10.1109\/TAES.2013.6404115","article-title":"Multi-Subaperture PGA for SAR Autofocusing","volume":"49","author":"Zhu","year":"2013","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_10","first-page":"26","article-title":"A Phase Gradient Autofocus Algorithm Based on Subaperture Phase Error Stitching","volume":"50","author":"Wen","year":"2021","journal-title":"Fire Control. Radar Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1109\/7.532283","article-title":"Motion compensation for ISAR via centroid tracking","volume":"32","author":"Itoh","year":"1996","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1109\/TGRS.2014.2377293","article-title":"Focused SAR Image Formation of Moving Targets Based on Doppler Parameter Estimation","volume":"53","author":"Noviello","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1072","DOI":"10.1109\/JSTARS.2015.2487685","article-title":"Analysis of a Maximum Likelihood Phase Estimation Method for Airborne Multibaseline SAR Interferometry","volume":"9","author":"Magnard","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Huang, X., Ji, K., Leng, X., Dong, G., and Xing, X. (2019). Refocusing Moving Ship Targets in SAR Images Based on Fast Minimum Entropy Phase Compensation. Sensors, 19.","DOI":"10.3390\/s19051154"},{"key":"ref_15","unstructured":"Zhu, Z., Qiu, X., and She, Z. (1966, January 20\u201322). ISAR motion compensation using modified Doppler centroid tracking method. Proceedings of the IEEE 1996 National Aerospace and Electronics Conference NAECON 1996, Dayton, OH, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1049\/ip-rsn:20045123","article-title":"Contrast maximization based technique for 2-D ISAR autofocusing. IEEE Proc","volume":"152","author":"Martorella","year":"2005","journal-title":"Radar Sonar Navig."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1240","DOI":"10.1109\/7.805442","article-title":"Autofocusing of ISAR images based on entropy minimization","volume":"35","author":"Xi","year":"1999","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2022.3188257","article-title":"Refocusing on SAR Ship Targets with Three-Dimensional Rotating Based on Complex-Valued Convolutional Gated Recurrent Unit","volume":"19","author":"Hua","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1109\/LGRS.2020.2967456","article-title":"DeepImaging: A Ground Moving Target Imaging Based on CNN for SAR-GMTI System","volume":"18","author":"Mu","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","first-page":"1","article-title":"Super-Resolution ISAR Imaging for Maneuvering Target Based on Deep-Learning-Assisted Time\u2013Frequency Analysis","volume":"60","author":"Qian","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"102832","DOI":"10.1016\/j.dsp.2020.102832","article-title":"SAR moving target imaging based on convolutional neural network","volume":"106","author":"Lu","year":"2020","journal-title":"Digit. Signal Process."},{"key":"ref_22","first-page":"1","article-title":"SAR Ground Moving Target Refocusing by Combining mRe\u00b3 Network and TV\u03b2-LSTM","volume":"60","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/2143\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:34:58Z","timestamp":1760121298000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/2143"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,14]]},"references-count":22,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23042143"],"URL":"https:\/\/doi.org\/10.3390\/s23042143","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2023,2,14]]}}}