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- W2557536369 abstract "Tomographic Synthetic aperture radar (Tomo-SAR) as an advanced 3-D imaging technique has been achieved great interest and development recently, especially the successful application of compressive sensing (CS) in this field. For simplicity, additive Gaussian noise has been often assumed to be identical independent distribution (i.i.d) to obtain the Cramer-Rao lower bound (CRLB) on elevation estimation. In this work, a realistic hybrid Cramer-Rao bound (HCRB) on elevation estimation is derived for CS Tomo-SAR in presence of the correlated noise. Concretely, a small random parameter representing the correlation of noises is introduced, which complies with the normalized Laplacian distribution in range of (−1, 1). Then the probability density function of observations conditioned the unknown deterministic sources parameter are correlated with a small nuisance parameter in non-diagonal elements of the noise covariance matrix. Computer simulations are performed for analyzing the proposed HCRB of elevation. Moreover, the root mean squares errors of two estimators based on CS have validated that the proposed HCRB approximates the realistic radar scenario better than CRLB." @default.
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- W2557536369 date "2016-09-01" @default.
- W2557536369 modified "2023-09-27" @default.
- W2557536369 title "The hybrid Cramér-Rao bounds on elevation in compressive sensing SAR tomography" @default.
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- W2557536369 doi "https://doi.org/10.1109/cosera.2016.7745714" @default.
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