Underlying Topography Inversion Using Dual Polarimetric TomoSAR
Underlying topography plays an important role in the national economic construction, military security, resource exploration and investigation. Since synthetic aperture radar tomography (TomoSAR) can achieve the three-dimensional imaging of forests, it has been widely used in underlying topography e...
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doaj-1891fa2b8a494b49a20614c3f449cca52021-07-01T00:14:35ZengMDPI AGSensors1424-82202021-06-01214117411710.3390/s21124117Underlying Topography Inversion Using Dual Polarimetric TomoSARXing Peng0Shilin Long1Youjun Wang2Qinghua Xie3Yanan Du4Xiong Pan5School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaSchool of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaSchool of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaSchool of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaSchool of Geographical Sciences, Guangzhou University, Guangzhou 510006, ChinaSchool of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, ChinaUnderlying topography plays an important role in the national economic construction, military security, resource exploration and investigation. Since synthetic aperture radar tomography (TomoSAR) can achieve the three-dimensional imaging of forests, it has been widely used in underlying topography estimation. At present, there are two kinds of TomoSAR based on the applied datasets: single polarimetric TomoSAR (SP-TomoSAR) and fully polarimetric TomoSAR (FP-TomoSAR). However, SP-TomoSAR cannot obtain the underlying topography accurately due to the lack of enough observations. FP-TomoSAR can improve the estimation accuracy of underlying topography. However, it requires high-cost data acquisition for the large-scale application. Thus, this paper proposes the dual polarimetric TomoSAR (DP-TomoSAR) as another suitable candidate to estimate the underlying topography because of its wide swath and multiple polarimetric observations. Moreover, three frequently used spectral estimation algorithms, namely, Beamforming, Capon and MUSIC, are used in DP-TomoSAR. For validation, a series of simulated experiments was carried out, and the airborne P-band multiple polarimetric SAR data over the Lope, Gabon was also acquired to estimate the underlying topography. The results suggest that DP-TomoSAR in HH & HV combination is more suitable to estimate underlying topography over forest areas than other DP combinations. Moreover, the estimation accuracy of DP-TomoSAR is slightly lower than that of FP-TomoSAR but is higher than that of SP-TomoSAR.https://www.mdpi.com/1424-8220/21/12/4117dual polarizationSAR tomography (TomoSAR)underlying topographybeamformingCaponMUSIC |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xing Peng Shilin Long Youjun Wang Qinghua Xie Yanan Du Xiong Pan |
spellingShingle |
Xing Peng Shilin Long Youjun Wang Qinghua Xie Yanan Du Xiong Pan Underlying Topography Inversion Using Dual Polarimetric TomoSAR Sensors dual polarization SAR tomography (TomoSAR) underlying topography beamforming Capon MUSIC |
author_facet |
Xing Peng Shilin Long Youjun Wang Qinghua Xie Yanan Du Xiong Pan |
author_sort |
Xing Peng |
title |
Underlying Topography Inversion Using Dual Polarimetric TomoSAR |
title_short |
Underlying Topography Inversion Using Dual Polarimetric TomoSAR |
title_full |
Underlying Topography Inversion Using Dual Polarimetric TomoSAR |
title_fullStr |
Underlying Topography Inversion Using Dual Polarimetric TomoSAR |
title_full_unstemmed |
Underlying Topography Inversion Using Dual Polarimetric TomoSAR |
title_sort |
underlying topography inversion using dual polarimetric tomosar |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2021-06-01 |
description |
Underlying topography plays an important role in the national economic construction, military security, resource exploration and investigation. Since synthetic aperture radar tomography (TomoSAR) can achieve the three-dimensional imaging of forests, it has been widely used in underlying topography estimation. At present, there are two kinds of TomoSAR based on the applied datasets: single polarimetric TomoSAR (SP-TomoSAR) and fully polarimetric TomoSAR (FP-TomoSAR). However, SP-TomoSAR cannot obtain the underlying topography accurately due to the lack of enough observations. FP-TomoSAR can improve the estimation accuracy of underlying topography. However, it requires high-cost data acquisition for the large-scale application. Thus, this paper proposes the dual polarimetric TomoSAR (DP-TomoSAR) as another suitable candidate to estimate the underlying topography because of its wide swath and multiple polarimetric observations. Moreover, three frequently used spectral estimation algorithms, namely, Beamforming, Capon and MUSIC, are used in DP-TomoSAR. For validation, a series of simulated experiments was carried out, and the airborne P-band multiple polarimetric SAR data over the Lope, Gabon was also acquired to estimate the underlying topography. The results suggest that DP-TomoSAR in HH & HV combination is more suitable to estimate underlying topography over forest areas than other DP combinations. Moreover, the estimation accuracy of DP-TomoSAR is slightly lower than that of FP-TomoSAR but is higher than that of SP-TomoSAR. |
topic |
dual polarization SAR tomography (TomoSAR) underlying topography beamforming Capon MUSIC |
url |
https://www.mdpi.com/1424-8220/21/12/4117 |
work_keys_str_mv |
AT xingpeng underlyingtopographyinversionusingdualpolarimetrictomosar AT shilinlong underlyingtopographyinversionusingdualpolarimetrictomosar AT youjunwang underlyingtopographyinversionusingdualpolarimetrictomosar AT qinghuaxie underlyingtopographyinversionusingdualpolarimetrictomosar AT yanandu underlyingtopographyinversionusingdualpolarimetrictomosar AT xiongpan underlyingtopographyinversionusingdualpolarimetrictomosar |
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1721349174897672192 |