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Received：12 September 2025，
Published：07 April 2026
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基于多基线干涉的层析合成孔径雷达TomoSAR（Synthetic Aperture Radar Tomography） 通过单天线重复航过或多天线单次航过获取多基线观测数据，在高程向形成第三维合成孔径，从而具备三维成像能力并实现森林三维结构的精细重建。然而，轨道间残余相位误差会引发层析谱的能量弥散与图像模糊，从而严重制约森林高度反演的精度与稳定性。此外，现有自聚焦方法在应对此问题时，常因相位误差中线性分量的干扰，产生不连续的层析剖面，不仅解译难度大，计算效率也较低。本文提出了一种基于子区域的对比度优化快速自聚焦SFCOA（Subarea Fast Contrast Optimization Autofocus）相位校正方法。该方法利用小尺度内相位误差的空间不变性，将传统逐像素优化转化为少量子区域的快速对比度最大化求解，显著降低了优化变量的维度；同时，借助相邻子区间的空间连续性构建链式初始化策略，大幅减少迭代次数与收敛时间。基于塞罕坝林场的机载P波段TomoSAR数据开展实验验证，结果表明所提SFCOA方法在不牺牲层析聚焦质量的前提下，其计算效率显著优于基于逐像元优化的PDCO方法，可将整景数据处理时间由小时级降至秒级。在森林垂直结构重建方面，与PSI、PGA及NC-PGA等方法相比，SFCOA所得层析成像结果的旁瓣水平更低以及主瓣展宽得到有效抑制，其层析功率谱的连续性也显著更优。在森林高度反演中，SFCOA相较于NC-PGA取得了更优的结果，其决定系数（
R
²）从0.516提升至0.609，平均绝对误差MAE（Mean Absolute Error）、平均绝对百分比误差（Mean Absolute Percentage Error，MAPE）与均方根误差 RMSE（Root Mean Square Error）分别从0.509 m、3.152%、0.627 m降至0.435 m、2.820%、0.526 m。所提出的SFCOA方法展现了效率与精度之间的优越平衡能力，为TomoSAR实现高精度三维森林测绘提供了一种高效的解决方案。
Synthetic Aperture Radar Tomography (TomoSAR)
which is based on multi-baseline interferometry
utilizes repeat-pass monostatic or single-pass multistatic data to synthesize an aperture in the elevation direction. This technique enables 3D imaging and the high-resolution reconstruction of forest structures. However
residual phase errors between tracks frequently lead to spectral energy dispersion and image blurring
significantly compromising the accuracy and stability of forest height retrieval. Moreover
existing phase error calibration methods require a high computational load for the tomographic imaging of large-scale forest scenarios.
To address the aforementioned issues
this study proposes a novel phase error calibration method
called Subarea Fast Contrast Optimization Autofocusing (SFCOA)
which enhances the efficiency and accuracy of TomoSAR imaging. This method leverages the spatial invariance of phase errors within local subareas to reduce the dimensionality of the optimization problem. By transforming traditional pixel-by-pixel optimization into an efficient contrast maximization task that is performed over a limited number of subareas
the method significantly lowers computational complexity. In addition
a chain initialization strategy based on spatial continuity between adjacent subareas minimizes the required iterations and substantially accelerates convergence.
The proposed SFCOA method is validated using airborne P-band TomoSAR data acquired over Saihanba Forest in Northern China. SFCOA is then compared with several representative phase calibration methods
including Phase Derivative Constrained Optimization (PDCO)
Phase-Shifting Interferometry (PSI)
Phase Gradient Autofocus (PGA)
and Network Construction (NC)-PGA. After phase error calibration
tomograms are generated using a Capon beamformer
and the resulting vertical profiles are evaluated against LiDAR measurements. The qualitative analysis of representative azimuth lines demonstrates that SFCOA achieves the narrowest main lobes
the lowest side lobes
and smooth vertical continuity in the reconstructed tomograms. By contrast
PDCO results exhibit vertical discontinuities. PSI only partially suppresses interference
with residual side lobes indicating incomplete phase error calibration. PGA achieves reasonable focus but suffers from contrast degradation near segment transitions
blurring the separation between canopy and ground reflections. Although NC-PGA reconstructs a continuous forest vertical structure
it remains inferior to SFCOA in terms of tomographic sharpness and peak localization accuracy.
Quantitative evaluations confirm the computational efficiency of SFCOA
which requires only 12.36 s to process the study area on a 2.5 GHz Intel CPU with 16 GB RAM
compared with 16.7 h for PDCO
388.97 s for PSI
28.25 s for PGA
and 45.39 s for NC-PGA. In forest height estimation
SFCOA also achieves superior accuracy
improving
R
2
from 0.516 to 0.609
mean absolute error from 0.509 m to 0.435 m
mean absolute percentage error from 3.152% to 2.820%
and root mean square error from 0.627 m to 0.526 m relative to NC-PGA.
In summary
SFCOA provides an accurate and computationally efficient phase error calibration solution for TomoSAR in forested environments. By combining subarea processing
derivative-constrained contrast optimization
and chain initialization
it achieves an effective balance between processing speed and reconstruction quality. The method exhibits strong potential for supporting high-precision 3D forest mapping and sustainable forest management.
Aghababaee H , Fornaro G and Schirinzi G . 2018 . Phase calibration based on phase derivative constrained optimization in multibaseline SAR tomography . IEEE Transactions on Geoscience and Remote Sensing , 56 ( 11 ): 6779 - 6791 [ DOI: 10.1109/TGRS.2018.2843447 http://dx.doi.org/10.1109/TGRS.2018.2843447 ]
Aghababaei H , Ferraioli G , Ferro-Famil L , Huang Y , D’Alessandro M M , Pascazio V , Schirinzi G and Tebaldini S . 2020 . Forest SAR tomography: principles and applications . IEEE Geoscience and Remote Sensing Magazine , 8 ( 2 ): 30 - 45 [ DOI: 10.1109/MGRS.2019.2963093 http://dx.doi.org/10.1109/MGRS.2019.2963093 ]
de Macedo K A C , Scheiber R and Moreira A . 2008 . An autofocus approach for residual motion errors with application to airborne repeat-pass SAR interferometry . IEEE Transactions on Geoscience and Remote Sensing , 46 ( 10 ): 3151 - 3162 [ DOI: 10.1109/TGRS.2008.924004 http://dx.doi.org/10.1109/TGRS.2008.924004 ]
Du Y N , Fu H Q , Liu L , Feng G C , Peng X and Wen D B . 2021 . Orbit error removal in InSAR/MTInSAR with a patch-based polynomial model . International Journal of Applied Earth Observation and Geoinformation , 102 : 102438 [ DOI: 10.1016/j.jag.2021.102438 http://dx.doi.org/10.1016/j.jag.2021.102438 ]
Feng D , An D X , Huang X T and Li Y L . 2019 . A phase calibration method based on phase gradient autofocus for airborne holographic SAR imaging . IEEE Geoscience and Remote Sensing Letters , 16 ( 12 ): 1864 - 1868 [ DOI: 10.1109/LGRS.2019.2911932 http://dx.doi.org/10.1109/LGRS.2019.2911932 ]
Gatti G , Tebaldini S , d’Alessandro M M and Rocca F . 2011 . ALGAE: a fast algebraic estimation of interferogram phase offsets in space-varying geometries . IEEE Transactions on Geoscience and Remote Sensing , 49 ( 6 ): 2343 - 2353 [ DOI: 10.1109/TGRS.2010.2091278 http://dx.doi.org/10.1109/TGRS.2010.2091278 ]
Iribe K , Papathanassiou K , Hajnsek I , Sato M and Yokota Y . 2010 . Coherent scatterer in forest environment : detection, properties and its applications// 2010 IEEE International Geoscience and Remote Sensing Symposium . Honolulu : IEEE: 3247 - 3250 [ DOI: 10.1109/IGARSS.2010.5651491 http://dx.doi.org/10.1109/IGARSS.2010.5651491 ]
Ji Y J and Zhang W F . 2022 . Research on retrieval of forest aboveground biomass by SAR technology . World Forestry Research , 35 ( 3 ): 32 - 39
姬永杰 , 张王菲 . 2022 . 森林地上生物量合成孔径雷达技术反演研究综述 . 世界林业研究 , 35 ( 3 ): 32 - 39 [ DOI: 10.13348/j.cnki.sjlyyj.2021.0113.y http://dx.doi.org/10.13348/j.cnki.sjlyyj.2021.0113.y ]
Kumar S , Joshi S K and Govil H . 2017 . Spaceborne PolSAR tomography for forest height retrieval . IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 10 ( 12 ): 5175 - 5185 [ DOI: 10.1109/JSTARS.2017.2741723 http://dx.doi.org/10.1109/JSTARS.2017.2741723 ]
Li L , Chen E X , Li Z Y , Feng Q and Zhao L . 2016 . A review on forest height and above ground biomass estimation based on synthetic aperture radar . Remote Sensing Technology and Application , 31 ( 4 ): 625 - 633
李兰 , 陈尔学 , 李增元 , 冯琦 , 赵磊 . 2016 . 合成孔径雷达森林树高和地上生物量估测研究进展 . 遥感技术与应用 , 31 ( 4 ): 625 - 633 [ DOI: 10.11873/j.issn.1004-0323.2016.4.0625 http://dx.doi.org/10.11873/j.issn.1004-0323.2016.4.0625 ]
Li W M , Li Z Y , Chen E X and Feng Q . 2014 . Status and development of tomographic SAR for forest vertical structural parameters inversion . Journal of Remote Sensing , 18 ( 4 ): 741 - 751
李文梅 , 李增元 , 陈尔学 , 冯琦 . 2014 . 层析SAR反演森林垂直结构参数现状及发展趋势 . 遥感学报 , 18 ( 4 ): 741 - 751 [ DOI: 10.11834/jrs.20143158 http://dx.doi.org/10.11834/jrs.20143158 ]
Li X W , Liang L , Guo H D and Huang Y . 2016 . Compressive sensing for multibaseline polarimetric SAR tomography of forested areas . IEEE Transactions on Geoscience and Remote Sensing , 54 ( 1 ): 153 - 166 [ DOI: 10.1109/TGRS.2015.2451992 http://dx.doi.org/10.1109/TGRS.2015.2451992 ]
Lu H L , Sun J L , Wang J L and Wang C L . 2022 . A novel phase compensation method for urban 3D reconstruction using SAR tomography . Remote Sensing , 14 ( 16 ): 4071 [ DOI: 10.3390/rs14164071 http://dx.doi.org/10.3390/rs14164071 ]
Lu H L , Zhang H , Fan H T , Liu D C , Wang J L , Wan X X , Zhao L , Deng Y K , Zhao F J and Wang R . 2021 . Forest height retrieval using P-band airborne multi-baseline SAR data: a novel phase compensation method . ISPRS Journal of Photogrammetry and Remote Sensing , 175 : 99 - 118 [ DOI: 10.1016/j.isprsjprs.2021.02.022 http://dx.doi.org/10.1016/j.isprsjprs.2021.02.022 ]
Pang Y , Li Z Y , Ju H B , Lu H , Jia W , Si L , Guo Y , Liu Q W , Li S M , Liu L X , Xie B B , Tan B X and Dian Y Y . 2016 . LiCHy: the CAF’s LiDAR, CCD and hyperspectral integrated airborne observation system . Remote Sensing , 8 ( 5 ): 398 [ DOI: 10.3390/rs8050398 http://dx.doi.org/10.3390/rs8050398 ]
Pardini M , Papathanassiou K , Bianco V and Iodice A . 2012 . Phase calibration of multibaseline SAR data based on a minimum entropy criterion // 2012 IEEE International Geoscience and Remote Sensing Symposium . Munich : IEEE: 5198 - 5201 [ DOI: 10.1109/IGARSS.2012.6352438 http://dx.doi.org/10.1109/IGARSS.2012.6352438 ]
Reigber A and Moreira A . 2000 . First demonstration of airborne SAR tomography using multibaseline L-band data . IEEE Transactions on Geoscience and Remote Sensing , 38 ( 5 ): 2142 - 2152 [ DOI: 10.1109/36.868873 http://dx.doi.org/10.1109/36.868873 ]
Reigber A , Prats P and Mallorqui J J . 2006 . Refined estimation of time-varying baseline errors in airborne SAR interferometry . IEEE Geoscience and Remote Sensing Letters , 3 ( 1 ): 145 - 149 [ DOI: 10.1109/LGRS.2005.860482 http://dx.doi.org/10.1109/LGRS.2005.860482 ]
Tebaldini S . 2010 . Single and multipolarimetric SAR tomography of forested areas: a parametric approach . IEEE Transactions on Geoscience and Remote Sensing , 48 ( 5 ): 2375 - 2387 [ DOI: 10.1109/TGRS.2009.2037748 http://dx.doi.org/10.1109/TGRS.2009.2037748 ]
Tebaldini S and Rocca F . 2009 . On the impact of propagation disturbances on SAR tomography: analysis and compensation // 2009 IEEE Radar Conference . Pasadena : IEEE: 1 - 6 [ DOI: 10.1109/RADAR.2009.4976991 http://dx.doi.org/10.1109/RADAR.2009.4976991 ]
Tebaldini S , Rocca F , d'Alessandro M M and Ferro-Famil L . 2016 . Phase calibration of airborne tomographic SAR data via phase center double localization . IEEE Transactions on Geoscience and Remote Sensing , 54 ( 3 ): 1775 - 1792 [ DOI: 10.1109/TGRS.2015.2488358 http://dx.doi.org/10.1109/TGRS.2015.2488358 ]
Wan J , Wang C C , Zhu J J and Fu H Q . 2024 . Research progress on tomographic SAR three-dimensional imaging methods and forest parameter inversion . National Remote Sensing Bulletin , 28 ( 3 ): 576 - 590
万杰 , 汪长城 , 朱建军 , 付海强 . 2024 . 层析SAR三维成像方法与森林参数反演研究进展 . 遥感学报 , 28 ( 3 ): 576 - 590 [ DOI: 10.11834/jrs.20222107 http://dx.doi.org/10.11834/jrs.20222107 ]
Wang L X , Xiang W , Song H J , Zhang H , Zheng M J , Wang J L , Xue F L , Ai Z Y and Deng Y K . 2025 . A novel phase calibration method for airborne P-, L-, and S-Band SAR tomography based on weighted phase gradient autofocus . IEEE Transactions on Geoscience and Remote Sensing , 63 : 5223920 [ DOI: 10.1109/TGRS.2025.3633509 http://dx.doi.org/10.1109/TGRS.2025.3633509 ]
Xu K P , Zhao L , Chen E X , Wang C C , Wan J , Fan Y X , Wang J , Ma Y M , Song Q , Huang P P and Li Z Y . 2025 . Forest height extraction based on TomoSAR technique using a novel phase error correction method . IEEE Transactions on Geoscience and Remote Sensing , 63 : 5216218 [ DOI: 10.1109/TGRS.2025.3589110 http://dx.doi.org/10.1109/TGRS.2025.3589110 ]
Yu Y H , Tebaldini S , Mariotti d’Alessandro M , Banda F , Lei Y and Liao M S . 2025 . Phase calibration of repeat-pass monostatic and bistatic airborne SAR tomographic data: a case study from the TomoSense campaign . IEEE Transactions on Geoscience and Remote Sensing , 63 : 5222014 [ DOI: 10.1109/TGRS.2025.3613167 http://dx.doi.org/10.1109/TGRS.2025.3613167 ]
Zeng G B , Xu H P , Wang Y and Liu W . 2024 . A novel method for airborne SAR tomography baseline error correction driven by small baseline interferometric phase . IEEE Transactions on Geoscience and Remote Sensing , 62 : 5225013 [ DOI: 10.1109/TGRS.2024.3478055 http://dx.doi.org/10.1109/TGRS.2024.3478055 ]
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