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A New Interferogram Flattening Method

Yanjie Zhang(1) and Prinet Veronique(1)

(1) National Laboratory of Pattern Recognition, the Institute of Automation, 100080, China

Abstract

It is well known that the interferometric phase is composed of the phase due to the real topography, the phase due to the flat earth (reference phase), the phase due to the noise, the phase due to the possible deformation. In the raw interferogram, they are entangled into each other. For the application of DInSAR which can be used to detect the deformation of the topography with a precision of cm-mm, the phase due to different parts must be isolated with each other. And this is especially true with the newly technique Permanent Scatters (PS) [3][4] [5]. So there is a strict precision requirement with the flattening technique. For a more clear explanation, the flattening problem is introduced first. The phase due to the flat earth must be removed completely. While the reference phase isn’t sensitive to the accuracy of the parameters such as the baseline, the tilt angle, the altitude of the satellite and so on, which means an imprecise parameters estimation will also has an approximating result, to a very high accuracy DInSAR application, this kind of phenomenon must be avoided. Otherwise the final result will be greatly noised by the imprecise parameters. To solve this problem, a new flattening method is introduced in this paper. The fringes caused by the flat earth will make the interferogram dense, and it adds the difficulty to do phase-unwrapping. Now there are many interferogram flattening methods which are based on the analysis of the flat earth phenomenon to derive the formula, or use track parameters to calculate the regular fringes. Due to the effect of the coherent noise, the flattened interferogram must be filtered, multi-look method is often used in this step. That is because these methods all do the job in the spatial domain. When using the track parameters to do flattening, it is very time consuming, because the Cartesian coordinate of each point has to be calculated, this must be done using the optimization method to solve the nonlinear function set first proposed by Curlander[6]. Fortunately the regular fringes can be represented using a high order polynomial[7]. So the calculation on few points are needed. But the precise track parameters are needed to do it. Otherwise the error of the coarse track parameters will lead to the shift of the positioning. We know that multi-look processing will have an effect on the coherence of the data. The accuracy of the phase is directly related with the coherence. In this paper a new method is proposed based on the knowledge of modern signal processing. The interferometric phase of the interferogram will be considered mainly as three parts: phase due to the flat earth, phase due to the topography and phase due to the noise (phase due to the atmosphere is included in it). From the knowledge of non-stationary signal processing, the interferomtric phase of the raw interferogram is a multi-component signal. The signal separation method is introduced in this paper.

References

1. Boualem Boashash, "Estimating and Interpreting The Instantaneous Frequency of a Signal-Part 1: Fundamentals", Proceedings of the IEEE, Vol.80, No.4, April, 1992 2. Boualem Boashash, "Estimating and Interpreting The Instantaneous Frequency of a Signal-Part 2: Algorithms and Applications", Proceedings of the IEEE, Vol.80, No.4, April, 1992 3. C. Colesanti, A. Ferretti, R. Locatelli, G.Savio, “Multi- platform Permanent Scatters Analysis: First Results”, 2nd GRSS/ISPRS Joint Workshop on “Data Fusion and Remote Sensing over Urban Areas” 4. Alessandro Ferretti, Claudio Prati, and Fabio Rocca, “Nonlinear Subsidence Rate Estimation Using Permanent Scatters in Differential SAR Interferometry”, IEEE Transactions On Geoscience and Remote Sensing, Vol.38, NO.5, September 20000 5. Alessandro Ferretti, Claudio Prati, and Fabio Rocca, “Permanent Scatters in SAR Interferometry”, IEEE Transactions On Geoscience and Remote Sensing, Vol.39, No.1, January 2001 6. John C. Curlander, “Location of Spaceborne SAR Imagery”, IEEE Transactions On Geoscience and Remote Sensing, Vol.GE-20, No.3, July 1982. 7. Christoph Reigber, Ye Xia, Hermann Kaufmann, Franz-Heinrich Massmann, et al, “Impact of Precise Orbits on SAR Interferometry”, Fringe’96 8. Zhu Daiyin, Zhu Zhaoda, Xie Qiucheng, “A Topography Adaptive Interferogram Filter Based on Local Frequency Estimation”, ACTA Electronic Sinica, Vol.30, No.12, Dec.2002 (in Chinese) 9. Umberto Spagnolini, “2-D Phase Unwrapping and Instantaneous Frequency Estimation”, IEEE Transactions On Geoscience and Remote Sensing, Vol.33, No.3, May 1995 10. Emmanuel Trouve, Jean-Marie Nicolas, and Henri Maitre, “Improving Phase Unwrapping Techniques by the Use of Local Frequency Estimates”, IEEE Transactions On Geoscience and Remote Sensing, Vol.36, No.6, November 1998

 

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry