不依赖人工定标器的全极化SAR定标研究进展

史磊; 杨杰; 李平湘; 杨乐; 赵伶俐

doi:10.11834/jrs.20219310

遥感遇上人工智能 | 浏览量 : 0 下载量: 284 CSCD: 0 更多指标

PDF
导出
分享
收藏
专辑

不依赖人工定标器的全极化SAR定标研究进展
Research process of full-polarimetric SAR calibration without using corner reflectors
2021年25卷第11期页码：2211-2219
纸质出版日期： 2021-11-07 ，
DOI： 10.11834/jrs.20219310

扫描看全文

史磊，杨杰，李平湘，杨乐，赵伶俐.2021.不依赖人工定标器的全极化SAR定标研究进展.遥感学报，25（11）： 2211-2219

Shi L，Yang J，Li P X，Yang L and Zhao L L. 2021. Research process of full-polarimetric SAR calibration without using corner reflectors. National Remote Sensing Bulletin， 25（11）：2211-2219
史磊，杨杰，李平湘，杨乐，赵伶俐.2021.不依赖人工定标器的全极化SAR定标研究进展.遥感学报，25（11）： 2211-2219 DOI： 10.11834/jrs.20219310.

Shi L，Yang J，Li P X，Yang L and Zhao L L. 2021. Research process of full-polarimetric SAR calibration without using corner reflectors. National Remote Sensing Bulletin， 25（11）：2211-2219 DOI： 10.11834/jrs.20219310.

摘要

极化定标是极化合成孔径雷达应用的前提。传统极化定标方法以地面布设的人工定标器为参考，通过极化畸变模型对系统误差进行求解与标定。然而，人工定标器价格昂贵、数量稀少，每次定标任务都需根据传感器过境方向、雷达视角等信息进行设备调整；此外，现代雷达系统工作波位多、入射角调节范围大，不同视角获取影像的定标参数也不相同，这对地面定标设备的布设精度、调整的时效性提出了更高要求。为了及时、快速地完成极化定标，如何以自然界中的某些特殊地物作为人工定标器的替代品来完成定标具有重大的科学价值。本文综述了近年来国内、外提出的不依赖人工定标器的SAR极化定标研究进展（即自主定标）。首先阐述了极化定标的基本流程与极化质量评价体系；然后对近年来高精度自主定标相关研究进行了梳理，根据技术特点将其分为基于自然地物约束的自主极化定标、基于似角反射器的自主极化定标两类，对不同算法适用性进行了分析；最后对未来的研究方向进行了展望。

Abstract

The polarimetric synthetic aperture (PolSAR) system transmits and receives electromagnetic waves with different polarization to acquire the image measurements. Polarimetric calibration (PolCAL) is a critical stage for PolSAR image quality improvement. The general calibration technique relies on the ground deployed active and passive corner reflectors (CRs) to solve the residual system errors after the internal calibration

such as the crosstalk

channel imbalance

Faraday Rotation Angle (FRA)

and so on. Although the best way to calibrate system distortion is based on ground reflectors

the manufacturing and deploying reflectors are time- and money-cost. For the common trihedral

rectangular

and pentagonal CRs

the angle bias of more than 1° between the metal plates would result in a 0.2-1 dB change of the Radar Cross Section (RCS). When the sensor wavelength increases

the ground-deployed CR length should also be enlarged to ensure that the RCS is high enough. A 1-m CR is usually required to calibrate a 0.05-m wavelength C-band satellite sensor

but a CR of more than 2 m is necessary to calibrate a 0.22-m wavelength L-band sensor. When calibrating the P-band BIOMASS

the CR length should be 5 m

which significantly increases the difficulties in the CRs manufacturing. Moreover

the azimuth and pitch angles of deployment reflector should be adjusted according the sensor pass direction and look angle. The current radar generally works on dozens of beam wave which demands heavy ground campaigns to accomplish with sensor configuration. During the operation period of the spaceborne SAR

the radiometric characteristics change with time

and the polarimetric distortions would change accordingly. Then it is of great importance to carry on the periodic calibration campaign. The regular performance of the calibration based on CRs undoubtedly increases the expenditure of time and effort. Therefore

it is vital to develop the calibration technique without using corner reflectors. This paper reports the recent research process of PolSAR calibration without using CRs. Firstly

we introduce the reason why non-reflector calibration technique is necessary and the evaluation criteria of image quality is given to help readers better understand the radar distortion. Secondly

we classify the recent non-reflector calibration methods into two categories as nature media-based calibration and corner reflector-like calibration. The properties of two categories are subsequently presented. The ways refer to the natural media

such as the in-scene vegetation in FRA-free area

to estimate the crosstalk and the cross-pol channel imbalance

while the co-pol channel imbalance may remain a constant or be solved using one or more CRs. In the scenes affected by FRA coupling with other distortions

a calibrator with no cross-polarized return may still be needed to increase the constraint for searching solutions. To get rid of the CRs

the special natural media or the CR-like point targets help to estimate the amplitude

phase of the co-pol channel imbalance and make outstanding achievements. Finally

the conclusion is given in the last section. The research on non-reflector calibration technique is meaningful and of great value for the SAR system with long wavelength.

关键词

合成孔径雷达（SAR）极化角反射器自主定标

Keywords

radar imagepolarimetriccorner reflectorcalibration

references

Ainsworth T L, Ferro-Famil L and Lee J S. 2006. Orientation angle preserving a posteriori polarimetric SAR calibration. IEEE Transactions on Geoscience and Remote Sensing, 44(4): 994-1003 [DOI: 10.1109/TGRS.2005.862508http://dx.doi.org/10.1109/TGRS.2005.862508]

Chang Y L, Li P X, Yang J, Zhao J Q, Zhao L L and Shi L. 2018. Polarimetric calibration and quality assessment of the GF-3 satellite images. Sensors, 18(2): 403 [DOI: 10.3390/s18020403http://dx.doi.org/10.3390/s18020403]

Chen J, Sato M and Yang J. 2011. Polarimetric calibration using distributed odd-bounce targets//2011 IEEE International Geoscience and Remote Sensing Symposium. Vancouver: IEEE: 1079-1082 [DOI: 10.1109/IGARSS.2011.6049383http://dx.doi.org/10.1109/IGARSS.2011.6049383]

Dai Y H, Feng L, Hou X J, Choi C Y, Liu J G, Cai X B, Shi L, Zhang Y L and Gibson L. 2019. Policy-driven changes in enclosure fisheries of large lakes in the yangtze plain: evidence from satellite imagery. Science of the Total Environment, 688: 1286-1297 [DOI: 10.1016/j.scitotenv.2019.06.179http://dx.doi.org/10.1016/j.scitotenv.2019.06.179]

Ferretti A, Prati C and Rocca F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20 [DOI: 10.1109/36.898661http://dx.doi.org/10.1109/36.898661]

Freeman A. 1992. SAR calibration: an overview. IEEE Transactions on Geoscience and Remote Sensing, 30(6): 1107-1121 [DOI: 10.1109/36.193786http://dx.doi.org/10.1109/36.193786]

Garthwaite M C, Nancarrow S, Hislop A, Thankappan M, Dawson J H and Lawrie S. 2015. The design of radar corner reflectors for the australian geophysical observing system: a single design suitable for InSAR deformation monitoring and sar calibration at multiple microwave frequency bands. Record 2015/03. Geoscience Australia [DOI: 10.11636/Record.2015.003http://dx.doi.org/10.11636/Record.2015.003]

Han B, Ding C B, Zhong L H, Liu J Y, Qiu X L, Hu Y X and Lei B. 2018. The GF-3 SAR data processor. Sensors, 18(3): 835 [DOI: 10.3390/s18030835http://dx.doi.org/10.3390/s18030835]

Jiang S, Qiu X L, Han B and Hu W L. 2018. A quality assessment method based on common distributed targets for GF-3 polarimetric sar data. Sensors, 18(3): 807 [DOI: 10.3390/s18030807http://dx.doi.org/10.3390/s18030807]

Kimura H. 2009. Calibration of polarimetric PALSAR imagery affected by faraday rotation using polarization orientation. IEEE Transactions on Geoscience and Remote Sensing, 47(12): 3943-3950 [DOI: 10.1109/TGRS.2009.2028692http://dx.doi.org/10.1109/TGRS.2009.2028692]

Lambers M and Kolb A. 2008. Automatic point target detection for interactive visual analysis of SAR images//IGARSS 2008-2008

IEEE International Geoscience and Remote Sensing Symposium. Boston: IEEE: II-903-II-906 [DOI: 10.1109/IGARSS.2008.4779141http://dx.doi.org/10.1109/IGARSS.2008.4779141]

Li Y, Hong W and Pottier E. 2015. Topography retrieval from single-pass POLSAR data based on the polarization-dependent intensity ratio. IEEE Transactions on Geoscience and Remote Sensing, 53(6): 3160-3177 [DOI: 10.1109/TGRS.2014.2369481http://dx.doi.org/10.1109/TGRS.2014.2369481]

Luscombe A P. 2004. Radarsat-2 SAR image quality and calibration operations. Canadian Journal of Remote Sensing, 30(3): 345-354 [DOI: 10.5589/m04-007http://dx.doi.org/10.5589/m04-007]

Morena L C, James K V and Beck J. 2004. An introduction to the RADARSAT-2 mission. Canadian Journal of Remote Sensing, 30(3): 221-234 [DOI: 10.5589/m04-004http://dx.doi.org/10.5589/m04-004]

Quegan S. 1994. A unified algorithm for phase and cross-talk calibration of polarimetric data-theory and observations. IEEE Transactions on Geoscience and Remote Sensing, 32(1): 89-99 [DOI: 10.1109/36.285192http://dx.doi.org/10.1109/36.285192]

Quegan S, Lomas M, Papathanassiou K P, Kim J S, Tebaldini S, Giudici D, Scagliola M, Guccione P, Dall J, Dubois-Fenandez P and Paillou P. 2018. Calibration challenges for the biomass P-band SAR instrument. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. Valencia: IEEE: 8575-8578 [DOI: 10.1109/IGARSS.2018.8518646http://dx.doi.org/10.1109/IGARSS.2018.8518646]

Quegan S and Lomas M R. 2015. The interaction between faraday rotation and system effects in synthetic aperture radar measurements of backscatter and biomass. IEEE Transactions on Geoscience and Remote Sensing, 53(8): 4299-4312 [DOI: 10.1109/TGRS.2015.2395138http://dx.doi.org/10.1109/TGRS.2015.2395138]

Sadeghi Z, Zoej M J V, Hooper A and Lopez-Sanchez J M. 2018. A new polarimetric persistent scatterer interferometry method using temporal coherence optimization. IEEE Transactions on Geoscience and Remote Sensing, 56(11): 6547-6555 [DOI: 10.1109/TGRS.2018.2840423http://dx.doi.org/10.1109/TGRS.2018.2840423]

Satake M, Matsuoka T, Umehara T, Nadai A, Uratsuka S and Fukuchi H. 2007. Polarimetric calibration experiment of ALOS PALSAR with polarization-selective dihedrals//2007 IEEE International Geoscience and Remote Sensing Symposium. Barcelona: IEEE: 1596-1598 [DOI: 10.1109/IGARSS.2007.4423117http://dx.doi.org/10.1109/IGARSS.2007.4423117]

Schneider R Z, Papathanassiou K P, Hajnsek I and Moreira A. 2006. Polarimetric and interferometric characterization of coherent scatterers in urban areas. IEEE Transactions on Geoscience and Remote Sensing, 44(4): 971-984 [DOI: 10.1109/TGRS.2005.860950http://dx.doi.org/10.1109/TGRS.2005.860950]

Schuler D L, Ainsworth T L, Lee J S and De Grandi G. 1998. Topographic mapping using polarimetric SAR data. International Journal of Remote Sensing, 19(1): 141-160 [DOI: 10.1080/014311698216477http://dx.doi.org/10.1080/014311698216477]

Shao Z F, Pan Y, Diao C Y and Cai J J. 2019. Cloud detection in remote sensing images based on multiscale features-convolutional neural network. IEEE Transactions on Geoscience and Remote Sensing, 57(6): 4062-4076 [DOI: 10.1109/TGRS.2018.2889677http://dx.doi.org/10.1109/TGRS.2018.2889677]

Shi L, Li P X, Yang J, Sun H W, Zhao L L and Zhang L P. 2020a. Polarimetric calibration for the distributed Gaofen-3 product by an improved unitary zero helix framework. ISPRS Journal of Photogrammetry and Remote Sensing, 160: 229-243 [DOI: 10.1016/j.isprsjprs.2019.12.003http://dx.doi.org/10.1016/j.isprsjprs.2019.12.003]

Shi L, Li P X, Yang J and Zhang L P. 2012. A statistical polarimetric decomposition solution based on the maximum-likelihood estimator. IEEE Geoscience and Remote Sensing Letters, 9(5): 861-865 [DOI: 10.1109/lgrs.2012.2185214http://dx.doi.org/10.1109/lgrs.2012.2185214]

Shi L, Li P X, Yang J, Zhang L P, Ding X L and Zhao L L. 2019. Co-polarization channel imbalance phase estimation by corner-reflector-like targets. ISPRS Journal of Photogrammetry and Remote Sensing, 147: 255-266 [DOI: 10.1016/j.isprsjprs.2018.12.001http://dx.doi.org/10.1016/j.isprsjprs.2018.12.001]

Shi L, Li P X, Yang J, Zhang L P, Ding X L and Zhao L L. 2020b. Polarimetric SAR calibration and residual error estimation when corner reflectors are unavailable. IEEE Transactions on Geoscience and Remote Sensing, 58(6): 4454-4471 [DOI: 10.1109/TGRS.2020.2964732http://dx.doi.org/10.1109/TGRS.2020.2964732]

Shi L, Sun W D, Yang J, Li P X and Lu L J. 2015. Building collapse assessment by the use of postearthquake Chinese VHR airborne SAR. IEEE Geoscience and Remote Sensing Letters, 12(10): 2021-2025 [DOI: 10.1109/LGRS.2015.2443018http://dx.doi.org/10.1109/LGRS.2015.2443018]

Shi L, Yang J and Li P X. 2014. Co-polarization channel imbalance determination by the use of bare soil. ISPRS Journal of Photogrammetry and Remote Sensing, 95: 53-67 [DOI: 10.1016/j.isprsjprs.2014.06.007http://dx.doi.org/10.1016/j.isprsjprs.2014.06.007]

Shi L, Zhang L F, Zhao L L, Yang J, Li P X and Zhang L P. 2013. The potential of linear discriminative laplacian eigenmaps dimensionality reduction in polarimetric SAR classification for agricultural areas. ISPRS Journal of Photogrammetry and Remote Sensing, 86: 124-135 [DOI: 10.1016/j.isprsjprs.2013.09.013http://dx.doi.org/10.1016/j.isprsjprs.2013.09.013]

Shimada M. 2011. Model-based polarimetric SAR calibration method using forest and surface-scattering targets. IEEE Transactions on Geoscience and Remote Sensing, 49(5): 1712-1733 [DOI: 10.1109/TGRS.2010.2090046http://dx.doi.org/10.1109/TGRS.2010.2090046]

Shimada M, Isoguchi O, Tadono T and Isono K. 2009. PALSAR radiometric and geometric calibration. IEEE Transactions on Geoscience and Remote Sensing, 47(12): 3915-3932 [DOI: 10.1109/TGRS.2009.2023909http://dx.doi.org/10.1109/TGRS.2009.2023909]

Siddique M A, Wegmüller U, Hajnsek I and Frey O. 2016. Single-look SAR tomography as an add-on to PSI for improved deformation analysis in urban areas. IEEE Transactions on Geoscience and Remote Sensing, 54(10): 6119-6137 [DOI: 10.1109/TGRS.2016.2581261http://dx.doi.org/10.1109/TGRS.2016.2581261]

Thompson A A, Luscombe A, James K and Fox P. 2008. RADARSAT-2 mission status: capabilities demonstrated and image quality achieved//7th European Conference on Synthetic Aperture Radar. Friedrichshafen: IEEE: 1-4

Touzi R and Shimada M. 2009. Polarimetric PALSAR calibration. IEEE Transactions on Geoscience and Remote Sensing, 47(12): 3951-3959 [DOI: 10.1109/TGRS.2009.2032176http://dx.doi.org/10.1109/TGRS.2009.2032176]

Ulander L M H. 2015. Trihedral corner reflector for polarimetric calibration of biomass//Proceedings of PolInSAR 2015. Frascati

Van Zyl J J. 1990. Calibration of polarimetric radar images using only image parameters and trihedral corner reflector responses. IEEE Transactions on Geoscience and Remote Sensing, 28(3): 337-348 [DOI: 10.1109/36.54360http://dx.doi.org/10.1109/36.54360]

Villa A, Iannini L, Giudici D, Monti-Guarnieri A and Tebaldini S. 2015. Calibration of SAR polarimetric images by means of a covariance matching approach. IEEE Transactions on Geoscience and Remote Sensing, 53(2): 674-686 [DOI: 10.1109/TGRS.2014.2326955http://dx.doi.org/10.1109/TGRS.2014.2326955]

Wang L, Yang J, Shi L, Li P X, Zhao L L and Deng S P. 2020. Impact of backscatter in Pol-InSAR forest height retrieval based on the multimodel random forest algorithm. IEEE Geoscience and Remote Sensing Letters, 17(2): 267-271 [DOI: 10.1109/LGRS.2019.2919449http://dx.doi.org/10.1109/LGRS.2019.2919449]

Wang Y T, Ainsworth T L and Lee J S. 2011. Assessment of system polarization quality for polarimetric sar imagery and target decomposition. IEEE Transactions on Geoscience and Remote Sensing, 49(5): 1755-1771 [DOI: 10.1109/TGRS.2010.2087342http://dx.doi.org/10.1109/TGRS.2010.2087342]

Zhang H, Lu W P, Zhang B, Chen J H and Wang C. 2013. Improvement of polarimetric SAR calibration based on the ainsworth algorithm for chinese airborne polsar data. IEEE Geoscience and Remote Sensing Letters, 10(4): 898-902 [DOI: 10.1109/LGRS.2012.2226864http://dx.doi.org/10.1109/LGRS.2012.2226864]

文章被引用时，请邮件提醒。

提交

暂无数据