Multibaseline synthetic aperture radar (SAR) interferometry can be exploited successfully for high-quality digital elevation model (DEM) reconstruction, provided that both noise and atmospheric effects are taken into account. A weighted combination of many uncorrelated topographic profiles strongly reduces the impact of phase artifacts on the final DEM. The key issue is weights selection. In the present article a wavelet domain approach is proposed. Taking advantage of the particular frequency trend of the atmospheric distortion, it is possible to estimate, directly from the data, noise and atmospheric distortion power for each interferogram. The available DEMs are then combined by means of a weighted average, carried out in the wavelet domain. This new approach provides a valuable tool not only for DEMs combination (improving accuracy), but for data evaluation and selection, since the phase error power is estimated for each interferogram. Results obtained using simulated and real data (ERS-1/2 TANDEM data of a test area around the Etna volcano, Sicily) are presented.
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