Optimal Baseline Design for Multibaseline InSAR Phase Unwrapping

Multibaseline (MB) synthetic aperture radar interferometry (InSAR) has the potential to improve the traditional single-baseline InSAR from the ill-posed problem to the well-posed problem. It is because MB InSAR phase unwrapping (PU) can take advantage of the baseline diversity to significantly incre...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2019-08, Vol.57 (8), p.5738-5750
Main Authors: Yu, Hanwen, Lee, Hyongki, Cao, Ning, Lan, Yang
Format: Article
Language:English
Subjects:
Atmospheric measurements
Baseline design
Bias
Cathode ray tubes
Continuity (mathematics)
Deformation
Deformation mechanisms
Design criteria
Ill posed problems
Integer programming
Interferometric synthetic aperture radar
Interferometry
Length measurement
Measurement
Methods
multibaseline (MB)
Noise measurement
Noise sensitivity
Optimization
Phase measurement
Phase unwrapping
phase unwrapping (PU)
Robustness
Robustness (mathematics)
SAR (radar)
Strain
synthetic aperture radar interferometry (InSAR)
Well posed problems
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Summary:Multibaseline (MB) synthetic aperture radar interferometry (InSAR) has the potential to improve the traditional single-baseline InSAR from the ill-posed problem to the well-posed problem. It is because MB InSAR phase unwrapping (PU) can take advantage of the baseline diversity to significantly increase the ambiguity intervals of interferometric phases, so it completely overcomes the limitation of the phase continuity assumption. However, due to the mathematical foundation of most of the MB PU methods, i.e., the Chinese remainder theorem (CRT), has poor measurement bias robustness (measurement bias could be caused by surface deformation, atmospheric artifact, and phase noise), CRT is sensitive to the normal baseline length. In other words, even if we choose the same CRT-based MB PU method, different system baseline lengths could result in different PU performances. Therefore, how to choose the baseline lengths to optimize CRT performance is crucial to all the CRT-based MB PU methods. In this paper, a nonlinear mixed-integer programming-based baseline design criterion (referred to NIP criterion) is proposed to maximize the measurement bias tolerance of the CRT-based MB PU. The optimality condition of the NIP criterion quantitatively provides important instructions for the CRT-based MB PU applications and offers significant guidance in the development of the practical MB InSAR system. The experiment results are shown to verify the effectiveness of the NIP criterion by using three representative CRT-based MB PU methods.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2019.2901873