On the Stochastic Model for InSAR Single Arc Point Scatterer Time Series

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

9 Downloads (Pure)


InSAR enables the estimation of displacements of (objects on) the earth's surface. To provide reliable estimates, both a stochastic and mathematical model are required. However, the intrinsic problem of InSAR is that both are unknown. Here we derive the Variance-Covariance Matrix (VCM) for double differenced phase observations for an arc, i.e., the phase difference between two points relative to a reference epoch. Using the Normalized Amplitude Dispersion we subdivide the time series in multiple partitions. The method results in a more realistic stochastic model, and consequently more realistic and reliable displacement parameters. The stochastic model also allows to make statements on the precision and reliability of the estimated parameters.

Original languageEnglish
Title of host publicationIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Electronic)9798350320107
Publication statusPublished - 2023
Event2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023) - Pasadena Convention Center, Pasadena, United States
Duration: 16 Jul 202321 Jul 2023

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)


Conference2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023)
Abbreviated titleIGARSS 2023
Country/TerritoryUnited States
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • InSAR
  • parameter estimation
  • Point Scatterers
  • stochastic model


Dive into the research topics of 'On the Stochastic Model for InSAR Single Arc Point Scatterer Time Series'. Together they form a unique fingerprint.

Cite this