TY - JOUR
T1 - A Novel Multiangle Images Association Algorithm Based on Supervised Areas for GNSS-Based InSAR
AU - Wang, Zhanze
AU - Liu, Feifeng
AU - Shang, Runze
AU - Zhou, Jingtian
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2023
Y1 - 2023
N2 - Global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR) systems can achieve 3-D deformation retrieval by associating multiangle images of different satellites. However, the difference in the scene radar cross section (RCS) and resolution cells makes multiangle images vary considerably. In addition, low resolution will further aggravate the difference in multiangle images. In this letter, a multiangle images association algorithm is proposed for GNSS-based InSAR systems. First, the supervised area is introduced to describe the areas of the same deformation based on the persistent scatter (PS) point. Then, the initial multiangle images association results are obtained by overlapping all PS points supervised areas of all satellites. Finally, the associated areas are normalized to obtain valid associated results. The raw data from eight Beidou satellites are used to prove the effectiveness of the proposed algorithm.
AB - Global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR) systems can achieve 3-D deformation retrieval by associating multiangle images of different satellites. However, the difference in the scene radar cross section (RCS) and resolution cells makes multiangle images vary considerably. In addition, low resolution will further aggravate the difference in multiangle images. In this letter, a multiangle images association algorithm is proposed for GNSS-based InSAR systems. First, the supervised area is introduced to describe the areas of the same deformation based on the persistent scatter (PS) point. Then, the initial multiangle images association results are obtained by overlapping all PS points supervised areas of all satellites. Finally, the associated areas are normalized to obtain valid associated results. The raw data from eight Beidou satellites are used to prove the effectiveness of the proposed algorithm.
KW - 3-D deformation retrieval
KW - global navigation satellite system-based synthetic aperture radar interferometry (GNSS-based InSAR)
KW - multiangle images association
KW - supervised areas
UR - http://www.scopus.com/inward/record.url?scp=85147277022&partnerID=8YFLogxK
U2 - 10.1109/LGRS.2023.3238505
DO - 10.1109/LGRS.2023.3238505
M3 - Article
AN - SCOPUS:85147277022
SN - 1545-598X
VL - 20
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
M1 - 4001705
ER -