On detection of the number of signals in presence of white noise
Journal of Multivariate Analysis
IEEE Transactions on Signal Processing
Estimation of the number of signals from features of the covariancematrix: a supervised approach
IEEE Transactions on Signal Processing
Multilook APES for multibaseline SAR interferometry
IEEE Transactions on Signal Processing
Reflectivity estimation for multibaseline interferometric radar imaging of layover extended sources
IEEE Transactions on Signal Processing
Source number estimators using transformed Gerschgorin radii
IEEE Transactions on Signal Processing
Analysis of the performance and sensitivity ofeigendecomposition-based detectors
IEEE Transactions on Signal Processing
On the behavior of information theoretic criteria for model orderselection
IEEE Transactions on Signal Processing
Model order selection in multi-baseline interferometric radar systems
EURASIP Journal on Applied Signal Processing
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This paper deals with the estimation of the number of components in a multibaseline interferometric synthetic aperture radar (InSAR) signal corrupted by multiplicative noise, in the presence of the layover phenomenon. The appearance of multiplicative noise, termed speckle in the radar jargon, 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 to estimate the number of signal components embedded in additive white noise. In this case, the problem of model order selection is equivalent to the estimation of the multiplicity of the smallest eigenvalues of the data covariance matrix. In presence of multiplicative noise, the signal eigenvalues spectrum changes. Consequently, the classical ITC methods operates under model mismatch. Nevertheless, before to look for other ad hoc methods, which could be difficult to derive or too heavy to implement, it is reasonable from an engineering point of view to investigate how the classical ITC methods are robust to the presence of multiplicative noise. Performance of the various ITC methods are analysed and compared under different operational scenarios. The relationship between performance and the eigenvalues distribution of the true covariance matrix is also investigated.