Indoor experiments on polarimetric SAR interferometry

Citation
L. Sagues et al., Indoor experiments on polarimetric SAR interferometry, IEEE GEOSCI, 38(2), 2000, pp. 671-684
Citations number
31
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
ISSN journal
01962892 → ACNP
Volume
38
Issue
2
Year of publication
2000
Part
1
Pages
671 - 684
Database
ISI
SICI code
0196-2892(200003)38:2<671:IEOPSI>2.0.ZU;2-Q
Abstract
A coherence optimization method, which makes use of polarimetry to enhance the quality of SAR interferograms, has been experimentally tested under lab oratory conditions in an anechoic chamber. By carefully selecting the polar ization in both images, the resulting interferogram exhibits an improved co herence above the standard HH or VV channel, This higher coherence produces a lower phase variance, thus estimating the underlying topography more acc urately. The potential improvement that this technique provides in the gene ration of digital elevation models (DEM) of non-vegetated natural surfaces has been observed for the first time on some artificial surfaces created wi th gravel. An experiment on a true outdoor DEM has not been accomplished ye t, but the first laboratory results show that the height error for an almos t planar surface can be drastically reduced within a wide range of baseline s by using the optimization algorithm. This algorithm leads to three possib le interferograms associated with statistically independent scattering mech anisms. The phase difference between those interferograms has been employed for extracting the height of vegetation samples. This retrieval technique has been tested on three different samples: maize, rice, and young fir tree s. The inverted heights are compared with ground truth for different freque ncy bands. The estimates are quite variable with frequency, but their compl ete physical justification is still in progress. Finally, an alternative si mplified scheme for the optimization is proposed. The new approach (called polarization subspace method) yields suboptimum results but is more intuiti ve and has been used for illustrating the working principle of the original optimization algorithm.