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An essential procedure in DS interferometry is phase estimation, which reconstructs a consistent phase series from all available interferograms. Influenced by the well-known suboptimality of coherence estimation, the performance of the state-of-the-art phase estimation algorithms is severely degraded. Previous research has addressed this problem by introducing the coherence bias correction technique. However, the precision of phase estimation is still insufficient because of the limited correction capabilities. In this paper, a modified phase estimation approach is proposed. Particularly, by incorporating the information on both interferometric coherence and the number of looks, a significant bias correction to each element of the coherence magnitude matrix is achieved. The bias-corrected coherence matrix is combined with advanced statistically homogeneous pixel selection and time series phase optimization algorithms to obtain the optimal phase series. Both the simulated and Sentinel-1 real data sets are used to demonstrate the superiority of this proposed approach over the traditional phase estimation algorithms. Specifically, the coherence bias can be corrected with considerable accuracy by the proposed scheme. The mean bias of coherence magnitude is reduced by more than 29%, and the standard deviation is reduced by more than 18% over the existing bias correction method. The proposed approach achieves higher accuracy than the current methods over the reconstructed phase series, including smoother interferometric phases and fewer outliers.<\/jats:p>","DOI":"10.3390\/rs15030613","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T02:52:21Z","timestamp":1674183141000},"page":"613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Modification to Phase Estimation for Distributed Scatterers in InSAR Data Stacks"],"prefix":"10.3390","volume":"15","author":[{"given":"Changjun","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"},{"name":"Northwest Land and Resources Research Center, Shaanxi Normal University, Xi\u2019an 710119, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunyun","family":"Dong","sequence":"additional","affiliation":[{"name":"Northwest Land and Resources Research Center, Shaanxi Normal University, Xi\u2019an 710119, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhao","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Earth Sciences and Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411201, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bangsen","family":"Tian","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7996-6745","authenticated-orcid":false,"given":"Jianmin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuo","family":"Gao","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuechi","family":"Yu","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zhu, X.X., Wang, Y.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"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Even, M., and Schulz, K. (2018). InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by New Advances. Remote Sens., 10.","DOI":"10.3390\/rs10050744"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Minh, D.H.T., Hanssen, R., and Rocca, F. (2020). Radar Interferometry: 20 Years of Development in Time Series Techniques and Future Perspectives. Remote Sens., 12.","DOI":"10.3390\/rs12091364"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1016\/j.rse.2005.08.002","article-title":"Mapping regional land displacements in the Venice coastland by an integrated monitoring system","volume":"98","author":"Teatini","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.jog.2016.05.003","article-title":"Vertical and horizontal displacements of Los Angeles from InSAR and GPS time series analysis: Resolving tectonic and anthropogenic motions","volume":"99","author":"Hu","year":"2016","journal-title":"J. Geodyn."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Qu, F., Lu, Z., Kim, J.-W., and Zheng, W. (2019). Identify and Monitor Growth Faulting Using InSAR over Northern Greater Houston, Texas, USA. Remote Sens., 11.","DOI":"10.3390\/rs11121498"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.rse.2010.08.008","article-title":"Potential of small-baseline SAR interferometry for monitoring land subsidence related to underground coal fires: Wuda (Northern China) case study","volume":"115","author":"Jiang","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.enggeo.2009.02.014","article-title":"InSAR analyses of terrain deformation near the Wieliczka Salt Mine, Poland","volume":"106","author":"Perski","year":"2009","journal-title":"Eng. Geol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.rse.2017.11.022","article-title":"Mapping landslide surface displacements with time series SAR interferometry by combining persistent and distributed scatterers: A case study of Jiaju landslide in Danba, China","volume":"205","author":"Dong","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhao, C., Kang, Y., Zhang, Q., Lu, Z., and Li, B. (2018). Landslide Identification and Monitoring along the Jinsha River Catchment (Wudongde Reservoir Area), China, Using the InSAR Method. Remote Sens., 10.","DOI":"10.3390\/rs10070993"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10346-017-0915-7","article-title":"The Maoxian landslide as seen from space: Detecting precursors of failure with Sentinel-1 data","volume":"15","author":"Intrieri","year":"2018","journal-title":"Landslides."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1111\/j.1365-246X.2004.02476.x","article-title":"The 2003 Bam (SE Iran) earthquake: Precise source parameters from satellite radar interferometry","volume":"159","author":"Wang","year":"2004","journal-title":"Geophys. J. Int."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1038\/s41561-018-0089-5","article-title":"Chilean megathrust earthquake recurrence linked to frictional contrast at depth","volume":"11","author":"Moreno","year":"2018","journal-title":"Nat. Geosci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00024-005-0005-y","article-title":"Combination of Precise Leveling and InSAR Data to Constrain Source Parameters of the M w = 6.5, 26 December 2003 Bam Earthquake","volume":"163","author":"Motagh","year":"2006","journal-title":"Pure Appl. Geophys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/S0273-1177(03)00483-6","article-title":"Detection of topographic changes associated with volcanic activities of Mt. Hossho using D-InSAR","volume":"33","author":"Tomiyama","year":"2004","journal-title":"Adv. Space Res."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"8323","DOI":"10.3390\/rs70708323","article-title":"StaMPS Improvement for Deformation Analysis in Mountainous Regions: Implications for the Damavand Volcano and Mosha Fault in Alborz","volume":"7","author":"Vajedian","year":"2015","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.earscirev.2019.03.009","article-title":"Monitoring volcano slope instability with Synthetic Aperture Radar: A review and new data from Pacaya (Guatemala) and Stromboli (Italy) volcanoes","volume":"192","author":"Schaefer","year":"2019","journal-title":"Earth-Sci. Rev."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2202","DOI":"10.1109\/36.868878","article-title":"Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry","volume":"38","author":"Ferretti","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.isprsjprs.2012.06.001","article-title":"An advanced algorithm for deformation estimation in non-urban areas","volume":"73","author":"Goel","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1109\/TGRS.2004.828196","article-title":"A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms","volume":"42","author":"Lanari","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1109\/TGRS.2011.2124465","article-title":"A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR","volume":"49","author":"Ferretti","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1029\/2008GL034654","article-title":"A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches","volume":"35","author":"Hooper","year":"2008","journal-title":"Geophys. Res. Lett."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5454","DOI":"10.1109\/TGRS.2013.2289370","article-title":"A Distributed Scatterer Interferometry Approach for Precision Monitoring of Known Surface Deformation Phenomena","volume":"52","author":"Goel","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1109\/TGRS.2011.2160644","article-title":"Repeat-Pass SAR Interferometry With Partially Coherent Targets","volume":"50","author":"Perissin","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7205","DOI":"10.1109\/TGRS.2014.2309346","article-title":"Joint-Scatterer Processing for Time-Series InSAR","volume":"52","author":"Lv","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2050","DOI":"10.1109\/TGRS.2014.2352853","article-title":"CAESAR: An Approach Based on Covariance Matrix Decomposition to Improve Multibaseline-Multitemporal Interferometric SAR Processing","volume":"53","author":"Fornaro","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1074","DOI":"10.1109\/TGRS.2015.2473818","article-title":"A Phase-Decomposition-Based PSInSAR Processing Method","volume":"54","author":"Cao","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.rse.2014.08.004","article-title":"Land subsidence characteristics of Bandung Basin as revealed by ENVISAT ASAR and ALOS PALSAR interferometry","volume":"154","author":"Ge","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3436","DOI":"10.1109\/TGRS.2008.2001756","article-title":"On the Exploitation of Target Statistics for SAR Interferometry Applications","volume":"46","author":"Guarnieri","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1012","DOI":"10.1109\/LSP.2007.904705","article-title":"Hybrid Cram\u00e9r\u2013Rao bounds for crustal displacement field estimators in SAR interferometry","volume":"14","author":"Guarnieri","year":"2007","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5637","DOI":"10.1109\/TGRS.2017.2711037","article-title":"Sequential Estimator: Toward Efficient InSAR Time Series Analysis","volume":"55","author":"Ansari","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4109","DOI":"10.1109\/TGRS.2018.2826045","article-title":"Efficient Phase Estimation for Interferogram Stacks","volume":"56","author":"Ansari","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1838","DOI":"10.1109\/LGRS.2015.2430752","article-title":"Mathematical Framework for Phase-Triangulation Algorithms in Distributed-Scatterer Interferometry","volume":"12","author":"Cao","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4543","DOI":"10.1109\/JSTARS.2019.2946729","article-title":"A Ground Surface Deformation Monitoring InSAR Method Using Improved Distributed Scatterers Phase Estimation","volume":"12","author":"Zhao","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"5671","DOI":"10.1109\/TGRS.2016.2566604","article-title":"Phase Estimation for Distributed Scatterers in InSAR Stacks Using Integer Least Squares Estimation","volume":"54","author":"Martins","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/j.isprsjprs.2018.12.008","article-title":"Mapping the Yellow River Delta land subsidence with multitemporal SAR interferometry by exploiting both persistent and distributed scatterers","volume":"148","author":"Zhang","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","first-page":"1","article-title":"A Fast Phase Optimization Approach of Distributed Scatterer for Multitemporal SAR Data Based on Gauss\u2013Seidel Method","volume":"19","author":"Song","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3914","DOI":"10.1109\/JSTARS.2021.3070750","article-title":"An Adaptive Phase Optimization Algorithm for Distributed Scatterer Phase History Retrieval","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2459","DOI":"10.1109\/TGRS.2013.2261996","article-title":"Hybrid Approach for Unbiased Coherence Estimation for Multitemporal InSAR","volume":"52","author":"Jiang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Vu, P., Breloy, A., Brigui, F., Yan, Y., and Ginolhac, G. (2022). Robust Phase Linking in InSAR. IEEE Trans. Geosci. Remote Sens., in review.","DOI":"10.1109\/TGRS.2023.3289338"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"6807","DOI":"10.1109\/TGRS.2014.2303516","article-title":"Adaptive Covariance Matrix Estimation for Multi-Baseline InSAR Data Stacks","volume":"52","author":"Schmitt","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1109\/TGRS.2014.2336237","article-title":"Fast Statistically Homogeneous Pixel Selection for Covariance Matrix Estimation for Multitemporal InSAR","volume":"53","author":"Jiang","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_45","first-page":"102792","article-title":"A statistically homogeneous pixel selection approach for adaptive estimation of multitemporal InSAR covariance matrix","volume":"110","author":"Zhao","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1109\/TGRS.2015.2471303","article-title":"Robust Estimators for Multipass SAR Interferometry","volume":"54","author":"Wang","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2022.3197423","article-title":"Cheap, Valid Regularizers for Improved Interferometric Phase Linking","volume":"19","author":"Zwieback","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_48","first-page":"1","article-title":"Reliable InSAR Phase History Uncertainty Estimates","volume":"60","author":"Zwieback","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_49","first-page":"1","article-title":"A New Likelihood Function for Consistent Phase Series Estimation in Distributed Scatterer Interferometry","volume":"60","author":"Wang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Even, M. (2021). A Study on Algorithms and Parameter Settings for DS Preprocessing. IEEE Geosci. Remote Sens. Symp., 3975\u20133978.","DOI":"10.1109\/IGARSS47720.2021.9553662"},{"key":"ref_51","first-page":"1","article-title":"Adapting InSAR Phase Linking for Seasonally Snow-Covered Terrain","volume":"60","author":"Eppler","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1942","DOI":"10.1109\/TGRS.2006.870440","article-title":"Interferometric SAR coherence magnitude estimation using second kind statistics","volume":"44","author":"Abdelfattah","year":"2006","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"186319","DOI":"10.1109\/ACCESS.2019.2961154","article-title":"Improved maximum likelihood estimation for optimal phase history retrieval of distributed scatterers in InSAR stacks","volume":"7","author":"Zhao","year":"2019","journal-title":"IEEE Access."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Li, S., Zhang, S., Li, T., Gao, Y., Zhou, X., Chen, Q., Zhang, X., and Yang, C. (2021). An Adaptive Weighted Phase Optimization Algorithm Based on the Sigmoid Model for Distributed Scatterers. Remote Sens., 13.","DOI":"10.3390\/rs13163253"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"R1","DOI":"10.1088\/0266-5611\/14\/4\/001","article-title":"Synthetic aperture radar interferometry","volume":"14","author":"Bamler","year":"1998","journal-title":"Inv. Probl."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1214\/aoms\/1177704250","article-title":"Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction)","volume":"3","author":"Goodman","year":"1963","journal-title":"Ann. Math. Stat."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1109\/36.739146","article-title":"Coherence estimation for SAR imagery","volume":"37","author":"Touzi","year":"1999","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Hanssen, R.F. (2001). Radar Interferometry Data Interpretation and Error Analysis, Kluwer.","DOI":"10.1007\/0-306-47633-9"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1109\/TGRS.2014.2333814","article-title":"Temporal Decorrelation in L-, C-, and X-band Satellite Radar Interferometry for Pasture on Drained Peat Soils","volume":"53","author":"Morishita","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1080\/01431169408954244","article-title":"Classification of multi-look polarimetric SAR imagery based on complex Wishart distribution","volume":"15","author":"Lee","year":"1992","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/613\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:11:50Z","timestamp":1760119910000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/3\/613"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,20]]},"references-count":60,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["rs15030613"],"URL":"https:\/\/doi.org\/10.3390\/rs15030613","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,1,20]]}}}