Contextual Information-Based Multichannel Synthetic Aperture Radar Interferometry: Addressing DEM reconstruction using contextual information

Interferometric synthetic aperture radar (InSAR) systems are capable of providing an estimate of the digital elevation model (DEM) of the imaged ground scene. This is usually done by means of a phase unwrapping (PU) operation. In the absence of additional regularity constraints, PU is an ill-posed problem, because the solution is not unique. Multichannel (MCh) techniques, using stacks of images of the same scene, can be used for restoring the solution uniqueness and reducing the effect of phase noise. Moreover, statistical techniques exploiting the contextual information contained in the data can provide satisfactory results. In this article, an overview of the main MCh statistical DEM reconstruction methods, developed both in the classical and in the Bayesian estimation framework, is presented. In particular, the effectiveness of the exploitation of contextual statistical models is shown by means of numerical experiments on simulated and real data sets.

[1]  Michael Eineder,et al.  Split band interferometry versus absolute ranging with wideband SAR systems , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[2]  Stan Z. Li,et al.  Markov Random Field Modeling in Image Analysis , 2001, Computer Science Workbench.

[3]  Fabio Rocca,et al.  Modeling Interferogram Stacks , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Vito Pascazio,et al.  Multifrequency InSAR height reconstruction through maximum likelihood estimation of local planes parameters , 2002, IEEE Trans. Image Process..

[5]  Richard M. Goldstein,et al.  Studies of multibaseline spaceborne interferometric synthetic aperture radars , 1990 .

[6]  F. Gini,et al.  Multibaseline cross-track SAR interferometry: a signal processing perspective , 2005, IEEE Aerospace and Electronic Systems Magazine.

[7]  Gilda Schirinzi,et al.  Multichannel interferometric SAR phase unwrapping using extended Kalman Smoother , 2013 .

[8]  S. Gómez,et al.  The triangle method for finding the corner of the L-curve , 2002 .

[9]  R. Bamler,et al.  Phase statistics of interferograms with applications to synthetic aperture radar. , 1994, Applied optics.

[10]  Fabrizio Lombardini,et al.  Optimum absolute phase retrieval in three-element SAR interferometer , 1998 .

[11]  Giampaolo Ferraioli,et al.  Multichannel Phase Unwrapping With Graph Cuts , 2009, IEEE Geoscience and Remote Sensing Letters.

[12]  Vito Pascazio,et al.  Maximum a posteriori estimation of height profiles in InSAR imaging , 2004, IEEE Geoscience and Remote Sensing Letters.

[13]  José M. N. Leitão,et al.  The ZπM algorithm: a method for interferometric image reconstruction in SAR/SAS , 2002, IEEE Trans. Image Process..

[14]  C. Werner,et al.  Satellite radar interferometry: Two-dimensional phase unwrapping , 1988 .

[15]  Giovanni Poggi,et al.  A Bayesian filtering technique for SAR interferometric phase fields , 2004, IEEE Transactions on Image Processing.

[16]  Fabio Rocca,et al.  Multibaseline phase unwrapping for INSAR topography estimation , 2001 .

[17]  P. Bahr,et al.  Sampling: Theory and Applications , 2020, Applied and Numerical Harmonic Analysis.

[18]  Howard A. Zebker,et al.  Phase unwrapping algorithms for radar interferometry: residue-cut, least-squares, and synthesis algorithms , 1998 .

[19]  A. Monti Guarnieri,et al.  Maximum likelihood multi-baseline Sar interferometry , 2006 .

[20]  Stephanie Thalberg,et al.  Interferometry And Synthesis In Radio Astronomy , 2016 .

[21]  V. Pascazio,et al.  DEM Reconstruction Accuracy in Multichannel SAR Interferometry , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Vito Pascazio,et al.  DEM Reconstruction Accuracy in Multichannel SAR Interferometry , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[23]  Mario Costantini,et al.  A novel phase unwrapping method based on network programming , 1998, IEEE Trans. Geosci. Remote. Sens..

[24]  Fuk K. Li,et al.  Synthetic aperture radar interferometry , 2000, Proceedings of the IEEE.

[25]  Giampaolo Ferraioli,et al.  Urban Digital Elevation Model Reconstruction Using Very High Resolution Multichannel InSAR Data , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[26]  V. Pascazio,et al.  Estimation of terrain elevation by multifrequency interferometric wide band SAR data , 2001, IEEE Signal Processing Letters.

[27]  Jeffrey A. Fessler,et al.  Regularized fieldmap estimation in MRI , 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

[28]  Weidong Yu,et al.  Integrated Denoising and Unwrapping of InSAR Phase Based on Markov Random Fields , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[29]  Vito Pascazio,et al.  Closed-Form Evaluation of the Second-Order Statistical Distribution of the Interferometric Phases in Dual-Baseline SAR Systems , 2010, IEEE Transactions on Signal Processing.

[30]  Otmar Loffeld,et al.  Phase Unwrapping for SAR Interferometry—A Data Fusion Approach by Kalman Filtering , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[31]  Mihai Datcu,et al.  Bayesian approaches to phase unwrapping: theoretical study , 2000, IEEE Trans. Signal Process..

[32]  Michael Eineder,et al.  A maximum-likelihood estimator to simultaneously unwrap, geocode, and fuse SAR interferograms from different viewing geometries into one digital elevation model , 2005, IEEE Transactions on Geoscience and Remote Sensing.