Title :
Analysis and statistical characterization of interferometric SAR signals based on the power spectral density function
Author_Institution :
German Aerosp. Center, Wessling, Germany
fDate :
5/1/2004 12:00:00 AM
Abstract :
Interferometric signal analysis is applied in many fields including filtering, parameter estimation, and interferogram processing optimization. Sample applications include the determination of terrain and orbit parameters, interferogram phase estimation, and optimal processing of synthetic aperture radar (SAR) interferograms. In this communication, the relevance of the power spectral density to interferometric SAR mode exploration and interferogram multilooking or filtering is discussed. The interferometric SAR modes include strip-map, scansar, and spotlight. For the verification of the multilooking characteristics of SAR interferograms, two frequently used filters serve as empirical reference. Based on a simplified interferometric system model and Guassian distributed scatterers, the power spectral density description is developed.
Keywords :
geophysical signal processing; interferometry; parameter estimation; remote sensing by radar; signal classification; statistical analysis; synthetic aperture radar; terrain mapping; Guassian distributed scatterers; filtering; interferogram multilooking; interferogram phase estimation; interferogram processing; interferometric SAR signals; interferometric signal analysis; interferometry; multilooking characteristics; optimal processing; optimization; orbit parameters; parameter estimation; power spectral density function; scansar; spotlight; statistical characterization; strip-map; synthetic aperture radar; terrain parameters; Density functional theory; Filtering; Filters; Large-scale systems; Phase estimation; Power system modeling; Reflectivity; Signal analysis; Synthetic aperture radar; Synthetic aperture radar interferometry; Filter; PSD; SAR; interferometry; multilooking; power spectral density; synthetic aperture radar;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
DOI :
10.1109/TGRS.2004.826554