Name
Title | ||
|---|---|---|
New algorithm for InSAR stack phase triangulation using integer least squares estimation |
Abstract | ||
|---|---|---|
Algorithms have been proposed in the recent years in order to retrieve all information available in interferometric stacks of SAR acquisitions with focus on distributed scatterers. One of the key steps in these algorithms - called phase triangulation, phase linking or phase multi-linking - is to optimally estimate filtered wrapped interferometric phases from all possible interferometric combinations preserving useful information and filtering noise. The advantages of these methods compared to conventional approaches are that the algorithm can be applied before phase unwrapping, and that it considers all possible interferograms. In this contribution we propose a new algorithm for phase triangulation based on the integer least squares (ILS) method. We model the phase triangulation problem as a system of linear observation equations. After computing the full covariance matrix of interferometric phases using a Monte-Carlo method, we use ILS to estimate the unknowns. The advantages of our method are that it is capable of considering the mutual correlation between all interferograms, and additionally provides as a output the precision of the estimates. Simulation results show that the proposed method works effectively and can optimally filter noise from interferometric stacks before unwrapping. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IGARSS.2013.6721301 | IGARSS |
Keywords | Field | DocType |
synthetic aperture radar,geophysics computing,full covariance matrix,insar stack phase triangulation,distributed scatterers (ds),linear observation equations,covariance matrices,remote sensing by radar,monte-carlo method,least squares approximations,monte carlo methods,interferometric synthetic aperture radar,insar,phase unwrapping,integer least squares estimation,radar interferometry,coherence matrix,time series analysis,monte carlo method,mathematical model,noise,vectors,decorrelation | Monte Carlo method,Interferometric synthetic aperture radar,Stack (abstract data type),Synthetic aperture radar,Computer science,Remote sensing,Algorithm,Filter (signal processing),Interferometry,Triangulation (social science),Covariance matrix | Conference |
ISSN | ISBN | Citations |
2153-6996 | 978-1-4799-1114-1 | 5 |
PageRank | References | Authors |
0.46 | 4 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sami Samiei-Esfahany | 1 | 16 | 2.91 |
| Ramon F. Hanssen | 2 | 107 | 28.92 |