Abstract
Interferogram phase unwrapping is one of the important data processing step in InSAR applications, however, it is affected by the high slope of terrain factors. In this paper, an improved constrained nonlinear least squares InSAR phase unwrapping method is proposed. First, we estimate the phase instantaneous frequency of the interferogram by the least squares method. Then, through the transformation between the phase instantaneous frequency and the phase gradient, we pre-estimate a phase gradient model considering terrain factors. Finally, using phase instantaneous frequency estimation (PIFE) model as the constraints of the nonlinear least squares phase, we propose the improved constrained nonlinear least squares (CNLS) phase unwrapping method. When compares with the other algorithms in the interferometric phase unwrapping experiments, the improved method is shown to be the most robust to noise caused by the terrain factors and to be the most suitable for phase unwrapping of the InSAR data in rugged and varied terrain regions.
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References
Liu, G.L., Hao, H.D., Yan, M.: Phase unwrapping algorithm by using Kalman filter based on topographic factors. Acta Geod. Cartogr. Sin. 40(3), 283–288 (2011)
Yu, H.W., Lan, Y., Yuan, Z.H.: Phase unwrapping in InSAR a review. IEEE Geosci. Remote Sens. Mag. 7(1), 40–58 (2019). https://doi.org/10.1109/MGRS.2018.2873644
Dudczyk, J., Kawalec, A.: Optimizing the minimum cost flow algorithm for the phase unwrapping process in SAR radar. Bull. Pol. Acad. Sci. Tech. Sci. 62(3), 511–516 (2014)
Man, L., Zibang, Z., Jingang, Z.: Phase unwrapping guided by instantaneous frequency for wavelet transform profilometry. J. Optoelectron. Laser 27(8), 853–862 (2016)
Xie, X.M., Zeng, Q.N.: Efficient and robust phase unwrapping algorithm based on unscented Kalman filter, the strategy of quantizing paths-guided map and pixel classification strategy. Appl. Opt. 54(31), 92–94 (2015)
Yandong, G., Shubi, Z., Tao, L.: Adaptive unscented Kalman filter phase unwrapping method and its application on Gaofen-3 interferometric SAR data. Sensors 1793(18), 853–862 (2018)
Haifeng, H., Qingsong, W.: A method of filtering and unwrapping SAR interferometric phase based on nonlinear phase model. Prog. Electromagn. Res. 144(1), 67–78 (2014)
Zhong, H., Tian, Z., Pan, H.: A combined phase unwrapping algorithm for InSAR interferogram in shared memory environment. In: International Congress on Image & Signal Processing. pp. 1504–1509 (2015). https://doi.org/10.1109/CISP.2015.7408122
Tao, Z., Liu, T., Liu, Z.D.: A novel DEM reconstruction strategy based on multi-frequency InSAR in highly sloped terrain. Sci. China Inf. Sci. 60(1), 1–3 (2017)
Zhiyong, W., Jixian, Z., Guoman, H.: Precise monitoring and analysis of the land subsidence in Jining coal mining area based on InSAR technique. J. China Univ. Min. Technol. 43(1), 169–174 (2014)
Weike, L., Guolin, L., Qiuxiang, T.: Nonlinear least squares phase unwrapping based on homotopy method. Sci. Surv. Mapp. 37(4), 126–128 (2012)
Syakrani, N., Baskoro, E.T., Mengko, T.L.: New weighting alternatives to MCFN phase unwrapping. Int. J. Tomogr. Simul. 28(3), 39–52 (2015)
Boyd, J.P.: Convergence and error theorems for Hermite function pseudo-RBFs: Interpolation on a finite interval by Gaussian-localized polynomials. Appl. Numer. Math. 87, 125–144 (2015)
Chen, C.W., Zebker, H.A.: Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models. IEEE Trans. Geosci. Remote Sens. 40(8), 1709–1719 (2002)
Acknowledgment
This work was supported by foundation of The National Natural Science Fund (41876202, 41774002); Natural Science Foundation of Shandong Province (ZR2017MD020).
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Zhang, X., Liu, W., Zheng, Y., Wang, Z. (2020). InSAR Phase Unwrapping with the Constrained Nonlinear Least Squares Method. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_58
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DOI: https://doi.org/10.1007/978-981-15-3308-2_58
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