Abstract
The reconstruction of digital surface models (DSMs) of urban areas from interferometric synthetic aperture radar (SAR) data is a challenging task. In particular the SAR inherent layover and shadowing effects need to be coped with by sophisticated processing strategies. In this paper, a maximum-likelihood estimation procedure for the reconstruction of DSMs from multi-aspect multi-baseline InSAR imagery is proposed. In this framework, redundant as well as contradicting observations are exploited in a statistically optimal way. The presented method, which is especially suited for single-pass SAR interferometers, is examined using test data consisting of experimental airborne millimeterwave SAR imagery. The achievable accuracy is evaluated by comparison to LiDAR-derived reference data. It is shown that the proposed estimation procedure performs better than a comparable non-statistical reconstruction method.
Original language | English |
---|---|
Pages (from-to) | 68-77 |
Number of pages | 10 |
Journal | ISPRS Journal of Photogrammetry and Remote Sensing |
Volume | 87 |
DOIs | |
State | Published - Jan 2014 |
Keywords
- Airborne
- Maximum likelihood estimation
- Multi-aspect
- Multi-baseline
- SAR interferometry (InSAR)
- Synthetic Aperture Radar (SAR)