Abstract
Abstract. This paper presents a novel single-pass airborne interferometric calibration method with a limited Number GCPs for InSAR digital elevation model (DEM) mapping. The proposed method is based on a rigorous three-dimensional model for a single-pass airborne InSAR system. The corrected InSAR parameters of baseline length, baseline inclination, near slant range, and Doppler centroid frequency, as well as phase offset, can be jointly solved via a unified optimization procedure in terms of the constructed three-dimensional geometric model using a limited number ground control points (GCPs). The proposed method is evaluated on real data of the CASMSAR system in X-band, the final DEMs generated by the calibration processing achieve a high accuracy level (1–3 m standard deviation), even in the presence of only 3–5 GCPs.
Highlights
The airborne InSAR system calibration is a necessary work for digital elevation model (DEM) mapping
This means that all the InSAR parameters which could cause phase errors have to be corrected before DEM mapping
Systematic phase errors are induced by geometric misregistration due to the existence of a squint angle, and statistical phase errors are a high frequencyerror that can be regarded as noise
Summary
The airborne InSAR system calibration is a necessary work for DEM mapping. This means that all the InSAR parameters which could cause phase errors have to be corrected before DEM mapping. From point of view of the high-precision DEM generation, airborne InSAR calibration involves the two aspects of InSAR parameter correction and phase-offset estimation. The SAIC method involve integrating the InSAR parameter correction and phase-offset estimation into a unified optimization procedure, in terms of the reconstructed three-dimensional geometric model using a limited number of GCPs. In the SAIC method, a rigorous three-dimensional model for the single-pass airborne InSAR system, instead of the traditional two-dimensional InSAR geometry model constructed, and the least squares (LS) principle is introduced to solve the built equations using only a few GCPs. The performance of the proposed SAIC method is evaluated using data from the Chinese CASMSAR system in the X-band from a flat area of Pucheng in China.
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