{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T09:11:06Z","timestamp":1769850666419,"version":"3.49.0"},"reference-count":24,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Multi-circular SAR(MCSAR) can obtain holographic three-dimensional (3D) images of interesting observation targets, which is a significant research field at present. For anisotropic scatterers, the multi-circular SAR incoherent 3D imaging strategy combines the principle of tomography SAR inversion to obtain better reconstruction results. However, in incoherent 3D imaging, the traditional L1-norm regularization method only considers sparse representation and reconstruction in the sub-aperture pixel unit along the elevation direction, and the target structural sparsity in the same pixel unit between adjacent sub-apertures is not considered. The hierarchical sparsity constraint method in multi-circular SAR 3D target reconstruction is proposed in this paper, the L1-norm regularization is used in sub-aperture elevation, and the L2,1-regularization-based group sparsity constraint is adopted in elevation of the adjacent sub-aperture. In this paper, the sparse group thresholding iterative method is proposed to reconstruct the 3D observed target image with MCSAR data. Compared with the traditional L1-norm regularization method and IAA-GLRT method for MCSAR target reconstruction in elevation, the proposed method in this paper could obtain clearer 3D observation target images, with fewer desultory points along the elevation direction. Detailed simulation data analysis and 3D imaging processing of real MCSAR data demonstrate the advantages of the proposed method.<\/jats:p>","DOI":"10.3390\/rs14163945","type":"journal-article","created":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T23:44:03Z","timestamp":1660607043000},"page":"3945","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-Circular SAR Three-Dimensional Image Formation via Group Sparsity in Adjacent Sub-Apertures"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3826-3944","authenticated-orcid":false,"given":"Weixing","family":"Yang","sequence":"first","affiliation":[{"name":"Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daiyin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1109\/LGRS.2013.2279236","article-title":"Polarimetric 3-D Reconstruction from Multicircular SAR at P-Band","volume":"11","author":"Ponce","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zelnio, E.G., Ferrara, M., Garber, F.D., Jackson, J.A., and Austin, C. (2009, January 16\u201317). Enhancement of multi-pass 3D circular SAR images using sparse reconstruction techniques. Proceedings of the Algorithms for Synthetic Aperture Radar Imagery XVI, Orlando, FL, USA.","DOI":"10.1117\/12.820256"},{"key":"ref_3","unstructured":"Ponce, O., Prats, P., Scheiber, R., Reigber, A., and Moreira, A. (2014, January 3\u20135). Study of the 3-D Impulse Response Function of Holographic SAR Tomography with Multicircular Acquisitions. Proceedings of the EUSAR 2014, 10th European Conference on Synthetic Aperture Radar, Berlin, Germany."},{"key":"ref_4","unstructured":"Moses, R.L., and Potter, L.C. (2005, January 7\u20138). Noncoherent 2D and 3D SAR reconstruction from wide-angle measurements. Proceedings of the 13th Annual Adaptive Sensor Array Processing Workshop, Lexington, MA, USA."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2142","DOI":"10.1109\/36.868873","article-title":"First demonstration of airborne SAR tomography using multibaseline L-band data","volume":"38","author":"Reigber","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","unstructured":"Zelnio, E.G., Ertin, E., Garber, F.D., Moses, R.L., and Potter, L.C. (2008, January 17\u201318). Multibaseline IFSAR for 3D target reconstruction. Proceedings of the Algorithms for Synthetic Aperture Radar Imagery XV, Orlando, FL, USA."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"6170","DOI":"10.1109\/TGRS.2016.2582959","article-title":"First Airborne Demonstration of Holographic SAR Tomography with Fully Polarimetric Multicircular Acquisitions at L-Band","volume":"54","author":"Ponce","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1109\/TGRS.2020.2994201","article-title":"Holographic SAR Tomography 3-D Reconstruction Based on Iterative Adaptive Approach and Generalized Likelihood Ratio Test","volume":"59","author":"Feng","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Sugavanam, N., and Ertin, E. (2022, January 21\u201325). Models of anisotropic scattering for 3D SAR reconstruction. Proceedings of the 2022 IEEE Radar Conference (RadarConf22), New York, NY, USA.","DOI":"10.1109\/RadarConf2248738.2022.9764209"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/MSP.2014.2311828","article-title":"Wide-Angle Synthetic Aperture Radar Imaging: Models and algorithms for anisotropic scattering","volume":"31","author":"Ash","year":"2014","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/MSP.2014.2312834","article-title":"Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing","volume":"31","author":"Varshney","year":"2014","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Stojanovic, I., Cetin, M., and Karl, W. (2008, January 16\u201320). Joint space aspect reconstruction of wide-angle SAR exploiting sparsity. Proceedings of the SPIE\u2014The International Society for Optical Engineering; International Society for Optical Engineering, Bellingham, WA, USA.","DOI":"10.1117\/12.786288"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4053","DOI":"10.1109\/TSP.2011.2161982","article-title":"Structured Compressed Sensing: From Theory to Applications","volume":"59","author":"Duarte","year":"2011","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"871","DOI":"10.1109\/LGRS.2012.2185482","article-title":"Multisignal Compressed Sensing for Polarimetric SAR Tomography","volume":"9","author":"Aguilera","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1109\/JSTSP.2010.2090128","article-title":"Sparse Signal Methods for 3-D Radar Imaging","volume":"5","author":"Austin","year":"2011","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1049\/iet-rsn.2009.0048","article-title":"Interferometric methods for three-dimensional target reconstruction with multipass circular SAR","volume":"4","author":"Ertin","year":"2010","journal-title":"IET Radar Sonar Navig."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zelnio, E.G., Austin, C.D., Garber, F.D., Ertin, E., and Moses, R.L. (2009, January 16\u201317). Sparse multipass 3D SAR imaging: Applications to the GOTCHA data set. Proceedings of the Algorithms for Synthetic Aperture Radar Imagery XVI, Orlando, FL, USA.","DOI":"10.1117\/12.820323"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/MSP.2007.914731","article-title":"An Introduction to Compressive Sampling","volume":"25","author":"Candes","year":"2008","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.1002\/cpa.20042","article-title":"An iterative thresholding algorithm for linear inverse problems with a sparsity constraint","volume":"57","author":"Daubechies","year":"2004","journal-title":"Commun. Pure Appl. Math."},{"key":"ref_20","unstructured":"Dudgeon, D., Lacoss, R., Lazott, C., and Verly, J. (1994, January 4\u20138). Use of persistent scatterers for model-based recognition. Proceedings of the SPIE\u2014The International Society for Optical Engineering; International Society for Optical Engineering, Bellingham, WA, USA."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Cai, T.T., Zhang, A.R., and Zhou, Y. (2022). Sparse Group Lasso: Optimal Sample Complexity, Convergence Rate, and Statistical Inference. IEEE Trans. Inf. Theory.","DOI":"10.1109\/TIT.2022.3175455"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"4183","DOI":"10.1109\/TSP.2011.2157912","article-title":"C-HiLasso: A Collaborative Hierarchical Sparse Modeling Framework","volume":"59","author":"Sprechmann","year":"2011","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ertin, E., Austin, C.D., Sharma, S., Moses, R.L., and Potter, L.C. (2008, January 10\u201311). GOTCHA experience report: Three-dimensional SAR imaging with complete circular apertures. Proceedings of the Algorithms for Synthetic Aperture Radar Imagery XIV, Orlando, FL, USA.","DOI":"10.1117\/12.723245"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zelnio, E.G., Casteel, J.C.H., Garber, F.D., Gorham, L.A., Minardi, M.J., Scarborough, S.M., Naidu, K.D., and Majumder, U.K. (2008, January 10\u201311). A challenge problem for 2D\/3D imaging of targets from a volumetric data set in an urban environment. Proceedings of the Algorithms for Synthetic Aperture Radar Imagery XIV, Orlando, FL, USA.","DOI":"10.1117\/12.731457"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/3945\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:08:30Z","timestamp":1760141310000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/16\/3945"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":24,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["rs14163945"],"URL":"https:\/\/doi.org\/10.3390\/rs14163945","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,14]]}}}