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The authors address the problem of estimating the number of components in a multibase line interferometric synthetic aperture radar (InSAR) signal, corrupted by complex correlated multiplicative noise, in the presence of the layover phenomenon. The appearance of multiplicative noise, termed ‘speckle’, makes this problem very atypical. in fact, all the approaches proposed in literature have been applied to constant amplitude sinusoidal signals. In particular, the information theoretic criteria (ITC) have been conceived for estimating the number of signal components embedded in additive white noise. In this case, the problem is equivalent to the estimation of the multiplicity of the smallest eigenvalues of the data covariance matrix. In the presence of multiplicative noise, the signal eigenvalues spectrum changes. Consequently, the classic ITC methods operate under model mismatch. in a previous work, the authors investigated their robustness to speckle. An ad hoc algorithm for model order selection, based on Capon and least squares methods is developed. Its performance is analysed via Monte Carlo simulation and compared with those of classic ITC. [ABSTRACT FROM AUTHOR]

An open problem of along-track interferometry (ATI) for synthetic aperture radar (SAR) sensing of ocean surface currents is the need of ancifiary wind information for inversion of Doppler centroid measurements, that have to be compensated for the propagation velocity of advancing and/or receding Bragg scatterers. We propose three classes of estimators which exploit multibaseline (MB) ATI acquisition and Doppler resolution for robust data inversion under different degrees of a priori information about the wind direction and the value of the characteristic Bragg frequency. Performance analysis and comparison with conventional ATI show that the proposed MB estimators can produce accurate velocity estimates in the absence of detailed ancillary data. [ABSTRACT FROM AUTHOR]