A Novel PS Selection and Registration Algorithm Based on Generalization Area for GNSS-Based InBSAR

TY - JOUR

T1 - A Novel PS Selection and Registration Algorithm Based on Generalization Area for GNSS-Based InBSAR

AU - Xu, Zhixiang

AU - Yao, Di

AU - Wang, Zhanze

AU - Liu, Feifeng

AU - Duan, Yunxuan

N1 - Publisher Copyright: © 2008-2012 IEEE.

PY - 2026

Y1 - 2026

N2 - Traditional permanent scatterer (PS) selection and registration algorithms suffer from significant errors in global navigation satellite system-based bistatic synthetic aperture radar (GNSS-based InBSAR) due to poor resolution, low SNR, accumulated baseline, and low position accuracy. In this article, a novel PS selection and registration algorithm based on generalization areas is proposed. First, the generalization area is introduced to adaptively handle the difference in resolution of multisatellite in a scene. Then, the PS preselection (pre-PS) association sequence is obtained according to the superposition of the generalization area, which replaces the traditional image registration algorithm. Finally, the final PS and interferometric phas are obtained according to the coherence and amplitude dispersion. The effectiveness of the proposed algorithm was demonstrated using raw data from eight navigation satellites monitored over a period of 32 consecutive days. The results showed an average accuracy of approximately 11.5 mm during 32 days.

AB - Traditional permanent scatterer (PS) selection and registration algorithms suffer from significant errors in global navigation satellite system-based bistatic synthetic aperture radar (GNSS-based InBSAR) due to poor resolution, low SNR, accumulated baseline, and low position accuracy. In this article, a novel PS selection and registration algorithm based on generalization areas is proposed. First, the generalization area is introduced to adaptively handle the difference in resolution of multisatellite in a scene. Then, the PS preselection (pre-PS) association sequence is obtained according to the superposition of the generalization area, which replaces the traditional image registration algorithm. Finally, the final PS and interferometric phas are obtained according to the coherence and amplitude dispersion. The effectiveness of the proposed algorithm was demonstrated using raw data from eight navigation satellites monitored over a period of 32 consecutive days. The results showed an average accuracy of approximately 11.5 mm during 32 days.

KW - Association sequence

KW - generalization area

KW - global navigation satellite system (GNSS)-based InBSAR

KW - permanent scatterer (PS)

UR - https://www.scopus.com/pages/publications/105022508534

U2 - 10.1109/JSTARS.2025.3633644

DO - 10.1109/JSTARS.2025.3633644

M3 - Article

AN - SCOPUS:105022508534

SN - 1939-1404

VL - 19

SP - 165

EP - 180

JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

ER -