An estimation method for InSAR interferometric phase using correlation weight joint subspace projection

Hai Li,Renbiao Wu

doi:10.1186/1687-6180-2013-27

Abstract

In this article, we propose a method to estimate the synthetic aperture radar interferometry (InSAR) interferometric phase based on the model of correlation weight joint pixel by using the joint subspace projection technique. In the method, the correlation weight joint data vector is constructed and the data vector can make the noise subspace dimension of the corresponding weight covariance matrix which is not affected by the coregistration error, thus avoiding the trouble of calculating the noise subspace dimension before estimating the InSAR interferometric phase. The method takes advantage of the coherence information of neighboring pixel pairs to auto-coregister the SAR images and employs the projection of the joint signal subspace onto the corresponding joint noise subspace to estimate the terrain interferometric phase. The method can auto-coregister the SAR images and reduce the interferometric phase noise simultaneously. Theoretical analysis and computer simulation results show that the method can provide accurate estimate of the interferometric phase (interferogram) even when the coregistration error reaches one pixel. The effectiveness of the method is verified via simulated data and real data.

Highlights

Synthetic aperture radar interferometry (InSAR) is an important remote sensing technique to retrieve the terrain digital elevation model [1,2]
Almost all the conventional InSAR interferometric phase estimation methods are based on interferogram filtering, such as pivoting mean filtering [10], pivoting median filtering [11], adaptive phase noise filtering [12]. and adaptive contoured window filtering [13]
The problem here is that when the quality of an interferogram is very poor due to a large coregistration error, it is very difficult for these methods to retrieve the true terrain interferometric phases

Summary

Introduction

Synthetic aperture radar interferometry (InSAR) is an important remote sensing technique to retrieve the terrain digital elevation model [1,2]. We propose a new method based on a correlation weight joint subspace projection to estimate the terrain interferometric phase accurately in the presence of large coregistration errors. In this method, the benefit from the correlation weight joint data vector is that the noise subspace. The second simulated data are the interferometric data pair of Mount Etna (the data are produced based on the SIR-C/X-SAR data acquired at X-band).b. the pivoting mean filtering the pivoting median filtering adaptive phase noise filtering adaptive contoured window filtering joint subspace projection the proposed method.

Conclusions

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