{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T18:09:18Z","timestamp":1769278158283,"version":"3.49.0"},"reference-count":36,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,9]],"date-time":"2023-06-09T00:00:00Z","timestamp":1686268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&amp;D Program of China","doi-asserted-by":"publisher","award":["2022YFB3901601"],"award-info":[{"award-number":["2022YFB3901601"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Airborne array tomographic synthetic aperture radar (TomoSAR) can acquire three-dimensional (3D) information of the observed scene in a single pass. In the process of airborne array TomoSAR data imaging, due to the disturbance of factors such as inconsistent antenna patterns and baseline errors, there are spatially varying amplitude-phase inconsistency errors in the multi-channel Single-Look-Complex (SLC) images. The existence of the errors degrades the quality of the 3D imaging results, which suffer from positioning errors, stray points, and spurious targets. In this paper, a new calibration method based on multiple prominent points is proposed to calibrate the errors of amplitude-phase inconsistency. Firstly, the prominent points are selected from the multi-channel SLC data. Then, the subspace decomposition method and maximum interference spectrum method are used to extract the multi-channel amplitude-phase inconsistency information at each point. The last step is to fit the varying curve and to compensate for the errors. The performance of the method is verified using actual data. The experimental results show that compared with the traditional fixed amplitude-phase inconsistency calibration method, the proposed method can effectively calibrate spatially varying amplitude-phase inconsistency errors, thus improving on the accuracy of 3D reconstruction results for large-scale scenes.<\/jats:p>","DOI":"10.3390\/rs15123032","type":"journal-article","created":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T01:59:07Z","timestamp":1686535147000},"page":"3032","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["The Calibration Method of Multi-Channel Spatially Varying Amplitude-Phase Inconsistency Errors in Airborne Array TomoSAR"],"prefix":"10.3390","volume":"15","author":[{"given":"Dawei","family":"Wang","sequence":"first","affiliation":[{"name":"National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fubo","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longyong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhua","family":"Li","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Yang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Microwave Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1109\/TAES.1985.310578","article-title":"Synthetic aperture radars","volume":"3","author":"Wiley","year":"1985","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4993","DOI":"10.1029\/JB091iB05p04993","article-title":"Topographic mapping from interferometric synthetic aperture radar observations","volume":"91","author":"Zebker","year":"1986","journal-title":"J. Geophys. Res. Solid Earth"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2234","DOI":"10.1109\/36.868881","article-title":"Generation of high precision DEMs of the Wadden Sea with airborne interferometric SAR","volume":"38","author":"Wimmer","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1080\/01431160210153039","article-title":"ERS tandem InSAR processing for DEM generation, glacier motion estimation and coherence analysis on Svalbard","volume":"24","author":"Eldhuset","year":"2003","journal-title":"Int. J. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1049\/iet-ipr.2018.5671","article-title":"High-resolution DEM building with SAR interferometry and high-resolution optical image","volume":"13","author":"Fizazi","year":"2019","journal-title":"IET Image Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1049\/ip-rsn:19951791","article-title":"Radar tomography for the generation of three-dimensional images","volume":"142","author":"Knaell","year":"1995","journal-title":"IEE Proc.-Radar Sonar Navig."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Klare, J., Wei\u00df, M., Peters, O., Brenner, A., and Ender, J. (August, January 31). ARTINO: A new high resolution 3D imaging radar system on an autonomous airborne platform. Proceedings of the 2006 IEEE International Symposium on Geoscience and Remote Sensing, Denver, CO, USA.","DOI":"10.1109\/IGARSS.2006.985"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Li, X., Zhang, F., Li, Y., Guo, Q., Wan, Y., Bu, X., Liu, Y., and Liang, X. (2021). An elevation ambiguity resolution method based on segmentation and reorganization of TomoSAR point cloud in 3D mountain reconstruction. Remote Sens., 13.","DOI":"10.3390\/rs13245118"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2019.2957215","article-title":"From interferometric to tomographic SAR: A review of synthetic aperture radar tomography-processing techniques for scatterer unmixing in urban areas","volume":"8","author":"Rambour","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2021.3077517","article-title":"Evaluation of nonparametric SAR tomography methods for urban building reconstruction","volume":"19","author":"Omati","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Peng, X., Li, X., Wang, C., Zhu, J., Liang, L., Fu, H., Du, Y., Yang, Z., and Xie, Q. (2019). SPICE-based SAR tomography over forest areas using a small number of P-band airborne F-SAR images characterized by non-uniformly distributed baselines. Remote Sens., 11.","DOI":"10.3390\/rs11080975"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MGRS.2019.2963093","article-title":"Forest SAR tomography: Principles and applications","volume":"8","author":"Aghababaei","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/TGRS.2015.2448686","article-title":"Geodetic SAR tomography","volume":"54","author":"Zhu","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3999","DOI":"10.1109\/JSTARS.2019.2940730","article-title":"Off-grid differential tomographic SAR and its application to railway monitoring","volume":"12","author":"Chai","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Li, X., Zhang, F., Liang, X., Li, Y., Guo, Q., Wan, Y., Bu, X., and Liu, Y. (2022). Fourfold Bounce Scattering-Based Reconstruction of Building Backs Using Airborne Array TomoSAR Point Clouds. Remote Sens., 14.","DOI":"10.3390\/rs14081937"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3839","DOI":"10.1109\/TGRS.2010.2048117","article-title":"Tomographic SAR inversion by L1 -norm regularization\u2014The compressive sensing approach","volume":"48","author":"Zhu","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"2403","article-title":"Linear array SAR 3-D imaging based on compressed sensing","volume":"32","author":"Wei","year":"2011","journal-title":"J. Astronaut."},{"key":"ref_18","first-page":"1","article-title":"Array 3-D SAR Tomography Using Robust Gridless Compressed Sensing","volume":"61","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bu, Y., Liang, X., Wang, Y., Zhang, F., and Li, Y. (2018). A unified algorithm for channel imbalance and antenna phase center position calibration of a single-pass multi-baseline TomoSAR system. Remote Sens., 10.","DOI":"10.3390\/rs10030456"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.isprsjprs.2022.06.005","article-title":"Error analysis and 3D reconstruction using airborne array InSAR images","volume":"190","author":"Hu","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2953","DOI":"10.1109\/TGRS.2010.2043738","article-title":"On the role of phase stability in SAR multibaseline applications","volume":"48","author":"Tebaldini","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","unstructured":"Werner, M., and Haeusler, M. (2001, January 9\u201313). X-SAR\/SRTM instrument phase error calibration. Proceedings of the IGARSS 2001, Scanning the Present and Resolving the Future, IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No. 01CH37217), Sydney, NSW, Australia."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1109\/TGRS.2009.2035308","article-title":"Final TerraSAR-X calibration results based on novel efficient methods","volume":"48","author":"Schwerdt","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1109\/TGRS.2015.2488358","article-title":"Phase calibration of airborne tomographic SAR data via phase center double localization","volume":"54","author":"Tebaldini","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"6779","DOI":"10.1109\/TGRS.2018.2843447","article-title":"Phase calibration based on phase derivative constrained optimization in multibaseline SAR tomography","volume":"56","author":"Aghababaee","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jiao, Z., Ding, C., Qiu, X., Zhou, L., Guo, J., and Han, D. (October, January 26). Channel Imbalance Calibration Method for Airborne TomoSAR System. Proceedings of the IGARSS 2020\u20142020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA.","DOI":"10.1109\/IGARSS39084.2020.9324025"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1864","DOI":"10.1109\/LGRS.2019.2911932","article-title":"A phase calibration method based on phase gradient autofocus for airborne holographic SAR imaging","volume":"16","author":"Feng","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.isprsjprs.2021.02.022","article-title":"Forest height retrieval using P-band airborne multi-baseline SAR data: A novel phase compensation method","volume":"175","author":"Lu","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Lu, H., Sun, J., Wang, J., and Wang, C. (2022). A Novel Phase Compensation Method for Urban 3D Reconstruction Using SAR Tomography. Remote Sens., 14.","DOI":"10.3390\/rs14164071"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1109\/LGRS.2014.2340898","article-title":"A novel scheme for ambiguous energy suppression in MIMO-SAR systems","volume":"12","author":"Wang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","unstructured":"Wei, S.J., Zhang, X.L., and Shi, J. (2014, January 13\u201318). Compressed sensing Linear array SAR 3-D imaging via sparse locations prediction. Proceedings of the 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, Canada."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/JRPROC.1947.231216","article-title":"The maximum range of a radar set","volume":"35","author":"Norton","year":"1947","journal-title":"Proc. IRE"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/36.898661","article-title":"Permanent scatterers in SAR interferometry","volume":"39","author":"Ferretti","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Yang, D.S., Chen, F., and Mo, S.Q. (2019). A novel real-valued DOA algorithm based on eigenvalue. Sensors, 20.","DOI":"10.3390\/s20010040"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1080\/01431161.2015.1030042","article-title":"3D surface reconstruction of layover areas in continuous terrain for multi-baseline SAR interferometry using a curve model","volume":"36","author":"Zhang","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Zhu, X.X., Wang, Y., Montazeri, S., and Ge, N. (2018). A review of ten-year advances of multi-baseline SAR interferometry using TerraSAR-X data. Remote Sens., 10.","DOI":"10.3390\/rs10091374"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3032\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:52:02Z","timestamp":1760125922000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/12\/3032"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,9]]},"references-count":36,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,6]]}},"alternative-id":["rs15123032"],"URL":"https:\/\/doi.org\/10.3390\/rs15123032","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,9]]}}}