Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm
Abstract
:1. Introduction
2. Deformation Estimation Model
3. Methodology
3.1. SA Algorithm for Deformation Estimation in TSInSAR
3.2. A Better Annealing Method
Algorithm 1 SA-based deformation estimation algorithm |
Input: the double difference phase of two pixels with a stack of interferograms. |
1: Initialize iterative variables: ; |
2: Calculate the object function value by (6); |
3: For |
4: Cool and calculate the temperature by (7); |
5: generate new solution and by (10), then calculate by (6); |
6: calculate the object function increment ; |
7: if < 0 |
8: accept the new solution and update ; |
9: else, |
10: calculate the acceptance probability by (11); |
11: generate a uniform distributed random number ; |
12: if |
13: accept the new solution and update ; |
14: end |
15: end |
Output: the final solution . |
4. Experiment
4.1. Test 1, Simulation Experiment
4.2. Test 2, Real Data Experiment
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Rosen, P.A.; Hensley, S.; Joughin, I.R.; Li, F.K.; Madsen, S.N.; Rodriguez, E.; Goldstein, R.M. Synthetic aperture radar interferometry. Proc. IEEE 2000, 88, 333–382. [Google Scholar] [CrossRef] [Green Version]
- Lu, Z.; Dzurisin, D. InSAR Imaging of Aleutian Volcanoes: Monitoring a Volcanic Arc from Space; Springer Praxis Books: Berlin, Germany, 2014; Volume 2014, pp. 1778–1786. [Google Scholar]
- Ferretti, A.; Prati, C.; Rocca, F. Permanent scatterers in SAR interferometry. In Proceedings of the International Geoscience and Remote Sensing Symposium, Hamburg, Germany, 28 June–2 July 1999; pp. 1–3. [Google Scholar]
- Ferretti, A.; Prati, C.; Rocca, F. Nonlinear subsidence rate estimation using permanent scatterers in differential SAR interferometry. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2202–2212. [Google Scholar] [CrossRef]
- Berardino, P.; Fornaro, G.; Lanari, R.; Sansosti, E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 2003, 40, 2375–2383. [Google Scholar] [CrossRef]
- Sansosti, E. A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms. IEEE Trans. Geosci. Remote Sens. 2004, 42, 1377–1386. [Google Scholar]
- Lauknes, T.R.; Zebker, H.A.; Larsen, Y. InSAR Deformation Time Series Using an L1-Norm Small-Baseline Approach. IEEE Trans. Geosci. Remote Sens. 2010, 49, 536–546. [Google Scholar] [CrossRef]
- Patrascu, C.; Popescu, A.A.; Datcu, M. SBAS and PS measurement fusion for enhancing displacement measurements. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 22–27 July 2012. [Google Scholar]
- Hooper, A. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys. Res. Lett. 2008, 35, 96–106. [Google Scholar] [CrossRef]
- Hooper, A.; Bekaert, D.; Spaan, K. Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics 2012, 514–517, 1–13. [Google Scholar] [CrossRef]
- Ferretti, A.; Fumagalli, A.; Novali, F.; Prati, C.; Rocca, F.; Rucci, A. A New Algorithm for Processing Interferometric Data-Stacks: SqueeSAR. IEEE Trans. Geosci. Remote Sens. 2011, 49, 3460–3470. [Google Scholar] [CrossRef]
- Fornaro, G.; Reale, D.; Serafino, F. Four-Dimensional SAR Imaging for Height Estimation and Monitoring of Single and Double Scatterers. IEEE Trans. Geosci. Remote Sens. 2009, 47, 224–237. [Google Scholar] [CrossRef]
- Hooper, A.; Zebker, H.; Segall, P.; Kampes, B. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers. Geophys. Res. Lett. 2004, 31. [Google Scholar] [CrossRef] [Green Version]
- Hooper, A. StaMPS/MTI Manual, Version 3.1. Delft Institute of Earth Observation and Space Systems; Delft University of Technology: Delft, The Netherlands, 2009. [Google Scholar]
- Zhang, L.; Ding, X.; Lu, Z. Modeling PSInSAR Time Series Without Phase Unwrapping. IEEE Trans. Geosci. Remote Sens. 2011, 49, 547–556. [Google Scholar] [CrossRef]
- Zhu, X.X.; Bamler, R. Superresolving SAR Tomography for Multidimensional Imaging of Urban Areas: Compressive sensing-based TomoSAR inversion. IEEE Signal Proc. Mag. 2014, 31, 51–58. [Google Scholar] [CrossRef]
- Werner, C.; Wegmuller, U.; Strozzi, T.; Wiesmann, A. Interferometric point target analysis for deformation mapping. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Toulouse, France, 21–25 July 2003; Volume 7, pp. 4362–4364. [Google Scholar]
- Kampes, B.M. Radar Interferometry: Persistent Scatterer Technique; German Aerospace Center (DLR): Cologne, Germany, 2006; pp. 31–39. ISBN 1-4020-4723-1.
- Costantini, M.; Falco, S.; Malvarosa, F.; Minati, F. A new method for identification and analysis of persistent scatterers in series of SAR images. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Boston, MA, USA, 7–11 July 2008; pp. 449–452. [Google Scholar]
- Costantini, M.; Minati, F.; Trillo, F.; Vecchioli, F. Enhanced PSP SAR interferometry for analysis of weak scatterers and high definition monitoring of deformations over structures and natural terrains. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia, 21–26 July 2013; pp. 876–879. [Google Scholar]
- Costantini, M.; Falco, S.; Malvarosa, F.; Minati, F.; Trillo, F.; Vecchioli, F. Persistent Scatterer Pair Interferometry: Approach and Application to COSMO-SkyMed SAR Data. Sel. Top. Appl. Earth Obs. Remote Sens. IEEE J. 2014, 7, 2869–2879. [Google Scholar] [CrossRef]
- Perissin, D.; Wang, T. Repeat-Pass SAR Interferometry with Partially Coherent Targets. IEEE Trans. Geosci. Remote Sens. 2011, 50, 271–280. [Google Scholar] [CrossRef]
- Blanco-Sanchez, P.; Mallorquí, J.J.; Duque, S.; Monells, D. The Coherent Pixels Technique (CPT): An Advanced DInSAR Technique for Nonlinear Deformation Monitoring. Pure Appl. Geophys. 2008, 165, 1167–1193. [Google Scholar] [CrossRef]
- Kirkpatrick, S.; Gelatt, C.D.; Vecchi, M.P. Optimization by Simulated Annealing. Science 1983, 220, 671–680. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hanssen, R.F. Radar Interferometry: Data Interpretation and Error Analysis; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2001; pp. 35–38. ISBN 0-306-47633-9. [Google Scholar]
- Van Leijen, F.J.; Hanssen, R.F. Persistent scatterer density improvement using adaptive deformation models. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain, 23–28 July 2007; pp. 2102–2105. [Google Scholar]
- Colesanti, C.; Ferretti, A.; Novali, F.; Prati, C.; Rocca, F. SAR monitoring of progressive and seasonal ground deformation using the permanent scatterers technique. IEEE Trans. Geosci. Remote Sens. 2003, 41, 1685–1701. [Google Scholar] [CrossRef]
- Kampes, M.; Hanssen, R.F. Ambiguity resolution for permanent scatterer interferometry. IEEE Trans. Geosci. Remote Sens. 2004, 42, 2446–2453. [Google Scholar] [CrossRef] [Green Version]
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Duan, W.; Zhang, H.; Wang, C. Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm. Sensors 2019, 19, 115. https://doi.org/10.3390/s19010115
Duan W, Zhang H, Wang C. Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm. Sensors. 2019; 19(1):115. https://doi.org/10.3390/s19010115
Chicago/Turabian StyleDuan, Wei, Hong Zhang, and Chao Wang. 2019. "Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm" Sensors 19, no. 1: 115. https://doi.org/10.3390/s19010115
APA StyleDuan, W., Zhang, H., & Wang, C. (2019). Deformation Estimation for Time Series InSAR Using Simulated Annealing Algorithm. Sensors, 19(1), 115. https://doi.org/10.3390/s19010115