تعداد نشریات | 161 |
تعداد شمارهها | 6,532 |
تعداد مقالات | 70,501 |
تعداد مشاهده مقاله | 124,098,781 |
تعداد دریافت فایل اصل مقاله | 97,206,383 |
On the evaluation of second order phase statistics in SAR interferogram stacks | ||
Earth Observation and Geomatics Engineering | ||
مقاله 1، دوره 1، شماره 1، شهریور 2017، صفحه 1-15 اصل مقاله (1.61 M) | ||
نوع مقاله: Original Article | ||
شناسه دیجیتال (DOI): 10.22059/eoge.2017.63865.1016 | ||
نویسندگان | ||
Sami Samiei-Esfahany* ؛ Ramon Hanssen | ||
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands | ||
چکیده | ||
During the last decades, time-series interferometric synthetic aperture radar (InSAR) has been emerged as a powerful technique to measure various surface deformation phenomena of the earth. The multivariate statistics of interferometric phase stacks plays an important role in the performance of different InSAR methodologies and also in the final quality description of InSAR derived products. The multivariate phase statistics are ideally described by a joint probability distribution function (PDF) of interferometric phases, whose closed-form evaluation in a generic form is very complicated and is not found in the literature. Focusing on the first two statistical moments, the stack phase statistics can be effectively described by a full (co)variance matrix. Although a closed-form expression of interferometric phase variances has been derived in literature for single-looked pixels, there is no such an expression for neither the variances of the multilooked pixels nor the covariances among interferometric phases. This paper presents two different approaches for evaluation of the full covariance matrix: one based on the numerical Monte-Carlo integration and the other based on an analytical approximation using nonlinear error propagation. We first, clarify on the noise components that are the subject of statistical models of this paper. Then, the complex statistics in SAR stacks and the phase statistics in a single interferogram are reviewed, followed by the phase statistics in InSAR stacks in terms of second statistical moments. The Monte-Carlo approach and the derivation of an analytical closed-form evaluation of InSAR second-order phase statistics are then introduced in details. Finally, the two proposed methods are validated against each other. | ||
کلیدواژهها | ||
InSAR؛ Covariance matrix؛ Radar interferometry؛ Phase statistics | ||
مراجع | ||
Ferretti, A., Fumagalli, A., Novali, F., Prati, C., Rocca, F., & Rucci, A. (2011). A new algorithm for processing interferometric data-stacks: SqueeSAR. IEEE Transactions on Geoscience and Remote Sensing, 49(9), 3460-3470. Guarnieri, A. M., & Tebaldini, S. (2008). On the exploitation of target statistics for SAR interferometry applications. IEEE Transactions on Geoscience and Remote Sensing, 46(11), 3436-3443. Bamler, R., & Hartl, P. (1998). Synthetic aperture radar interferometry. Inverse problems, 14(4), R1. Tough, R. J. A., Blacknell, D., & Quegan, S. (1995, June). A statistical description of polarimetric and interferometric synthetic aperture radar data. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences (Vol. 449, No. 1937, pp. 567-589). The Royal Society. Just, D., & Bamler, R. (1994). Phase statistics of interferograms with applications to synthetic aperture radar. Applied optics, 33(20), 4361-4368. Lee, J. S., Hoppel, K. W., Mango, S. A., & Miller, A. R. (1994). Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery. IEEE Transactions on Geoscience and Remote Sensing, 32(5), 1017-1028. Rodriguez, E., & Martin, J. M. (1992, April). Theory and design of interferometric synthetic aperture radars. In IEE Proceedings F (Radar and Signal Processing) (Vol. 139, No. 2, pp. 147-159). IET Digital Library. Sarabandi, K. (1992). Derivation of phase statistics from the Mueller matrix. Radio Science, 27(05), 553-560. Eineder, M., & Adam, N. (2005). A maximum-likelihood estimator to simultaneously unwrap, geocode, and fuse SAR interferograms from different viewing geometries into one digital elevation model. IEEE Transactions on Geoscience and Remote Sensing, 43(1), 24-36. Cuenca, M. C., Hooper, A. J., & Hanssen, R. F. (2011). A new method for temporal phase unwrapping of persistent scatterers InSAR time series. IEEE Transactions on Geoscience and Remote Sensing, 49(11), 4606-4615. Lucido, M., Meglio, F., Pascazio, V., & Schirinzi, G. (2010). Closed-form evaluation of the second-order statistical distribution of the interferometric phases in dual-baseline SAR systems. IEEE Transactions on Signal Processing, 58(3), 1698-1707. Hanssen, R. F. (2001). Radar interferometry: data interpretation and error analysis (Vol. 2). Springer Science & Business Media. Ferretti, A., Prati, C., & Rocca, F. (2001). Permanent scatterers in SAR interferometry. IEEE Transactions on geoscience and remote sensing, 39(1), 8-20. Kampes, B. M., & Hanssen, R. F. (2004). Ambiguity resolution for permanent scatterer interferometry. IEEE Transactions on Geoscience and Remote Sensing, 42(11), 2446-2453. Danvenport Jr, W. B. (1970). Probability and random processes and introduction for applied scientists and engineers (No. 519.2 D3). Madsen, S. N. (1986). Speckle theory: Modelling, analysis, and applications related to synthetic aperture radar data. Ph. D thesis, Electromagnetics Institute, 62. Goodman, J. W. (1976). Some fundamental properties of speckle. JOSA, 66(11), 1145-1150. Hannan, E. J., & Thomson, P. J. (1971). The estimation of coherence and group delay. Biometrika, 58(3), 469-481. Born, M., & Wolf, E. (2013). Principles of optics: electromagnetic theory of propagation, interference and diffraction of light. Elsevier. Foster, M. R., & Guinzy, N. J. (1967). The coefficient of coherence: its estimation and use in geophysical data processing. Geophysics, 32(4), 602-616. Papoulis, A. (1985). Random Variables and Stochastic Processes. Goodman, N. R. (1963). Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction). The Annals of mathematical statistics, 34(1), 152-177. Barber, B. C. (1993). The phase statistics of a multichannel radar interferometer. Waves in random media, 3(4), 257-266. Gradshteyn, I. S., & Ryzhik, I. M. (2014). Table of integrals, series, and products. Academic press. Joughin, L. R., & Winebrenner, D. P. (1994, August). Effective number of looks for a multilook interferometric phase distribution. In Geoscience and Remote Sensing Symposium, 1994. IGARSS'94. Surface and Atmospheric Remote Sensing: Technologies, Data Analysis and Interpretation., International(Vol. 4, pp. 2276-2278). IEEE. Oberhettinger, F. (1972). Hypergeometric functions. Handbook of mathematical functions, 556. Abramowitz, M., & Stegun, I. A. (1966). Handbook of mathematical functions. Applied mathematics series, 55(62), 39. Quegan, S., Dutra, L. V., & Grover, K. (1994). Phase measurements in MAESTRO polarimetric data from the UK test sites. International Journal of Remote Sensing, 15(14), 2719-2736. Agram, P. S., & Simons, M. (2015). A noise model for InSAR time series. Journal of Geophysical Research: Solid Earth, 120(4), 2752-2771. Ripley, B. D. (2009). Stochastic simulation (Vol. 316). John Wiley & Sons. Kalos, M. H., & Whitlock, P. A. (2008). Monte carlo methods. John Wiley & Sons. Liu, J. S. (2008). Monte Carlo strategies in scientific computing. Springer Science & Business Media. Gundlich, B., Koch, K. R., & Kusche, J. (2003). Gibbs sampler for computing and propagating large covariance matrices. Journal of Geodesy, 77(9), 514-528. Alkhatib, H. (2008). On Monte Carlo methods with applications to the current satellite gravity missions (Doctoral dissertation, Universität Bonn). MATLAB, version R2014a, statistical toolbox. Natick, Massachusetts: The MathWorks Inc., 2014. Gentle, J. E. (2006). Random number generation and Monte Carlo methods. Springer Science & Business Media. Fishman, G. (2013). Monte Carlo: concepts, algorithms, and applications. Springer Science & Business Media. Rocca, F. (2007). Modeling interferogram stacks. IEEE Transactions on Geoscience and Remote Sensing, 45(10), 3289-3299. De Zan, F., Zonno, M., & López-Dekker, P. (2015). Phase inconsistencies and multiple scattering in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 53(12), 6608-6616. Mandic, D. P., & Goh, V. S. L. (2009). Complex valued nonlinear adaptive filters: noncircularity, widely linear and neural models (Vol. 59). John Wiley & Sons. Neeser, F. D., & Massey, J. L. (1993). Proper complex random processes with applications to information theory. IEEE transactions on information theory, 39(4), 1293-1302. Picinbono, B., & Bondon, P. (1997). Second-order statistics of complex signals. IEEE Transactions on Signal Processing, 45(2), 411-420. Schreier, P. J., & Scharf, L. L. (2003). Second-order analysis of improper complex random vectors and processes. IEEE Transactions on Signal Processing, 51(3), 714-725 Reed, I. (1962). On a moment theorem for complex Gaussian processes. IRE Transactions on Information Theory, 8(3), 194-195. Krishnan, V. (2015). Probability and random processes. John Wiley & Sons. | ||
آمار تعداد مشاهده مقاله: 698 تعداد دریافت فایل اصل مقاله: 670 |