A novel multitemporal insar model for joint estimation of deformation rates and orbital errors

Lei Zhang, Xiaoli Ding, Zhong Lu, Hyung Sup Jung, Jun Hu, Guangcai Feng

Research output: Contribution to journalArticlepeer-review

80 Scopus citations


Orbital errors, characterized typically as longwavelength artifacts, commonly exist in interferometric synthetic aperture radar (InSAR) imagery as a result of inaccurate determination of the sensor state vector. Orbital errors degrade the precision of multitemporal InSAR products (i.e., ground deformation). Although research on orbital error reduction has been ongoing for nearly two decades and several algorithms for reducing the effect of the errors are already in existence, the errors cannot always be corrected efficiently and reliably. We propose a novel model that is able to jointly estimate deformation rates and orbital errors based on the different spatialoral characteristics of the two types of signals. The proposed model is able to isolate a long-wavelength ground motion signal from the orbital error even when the two types of signals exhibit similar spatial patterns. The proposed algorithm is efficient and requires no ground control points. In addition, the method is built upon wrapped phases of interferograms, eliminating the need of phase unwrapping. The performance of the proposed model is validated using both simulated and real data sets. The demo codes of the proposed model are also provided for reference.

Original languageEnglish
Article number6656824
Pages (from-to)3529-3540
Number of pages12
JournalIEEE Transactions on Geoscience and Remote Sensing
Issue number6
StatePublished - Jun 2014


  • Interferometric synthetic aperture radar (SAR) (InSAR)
  • SAR
  • Sparse matrix
  • least squares
  • orbital error


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