Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark...Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.展开更多
Global navigation satellite system（GNSS） can be employed as a transmitter to composite bistatic synthetic aperture radar（BiSAR）.As GNSS signal is quite different from the traditional radar signal,modified spectral...Global navigation satellite system（GNSS） can be employed as a transmitter to composite bistatic synthetic aperture radar（BiSAR）.As GNSS signal is quite different from the traditional radar signal,modified spectral analysis（SPECAN） algorithm is proposed and applied in the BiSAR system.The modifications include Doppler centroid compensation,range curve correction and azimuth processing method.The modified SPECAN algorithm solves the imaging problem under the condition of huge range migration,long synthetic aperture time and phase-coded signal.The proposed algorithm is verified by experiment results.展开更多
基金The National Science and Technology Support Project under contract No.2014BAB12B02the Natural Science Foundation of Liaoning Province under contract No.201602042
文摘Oil spills pose a major threat to ocean ecosystems and their health. Synthetic aperture radar（SAR） sensors can detect oil spills on the sea surface. These oil spills appear as dark spots in SAR images. However, dark formations can be caused by a number of phenomena. It is aimed to distinguishing oil spills or look-alike objects. A novel method based on a bidimensional empirical mode decomposition is proposed. The selected dark formations are first decomposed into several bidimensional intrinsic mode functions and the residue. Subsequently, 64 dimension feature sets are calculated using the Hilbert spectral analysis and five new features are extracted with a relief algorithm. Mahalanobis distances are then used for classification. Three data sets containing oil spills or look-alikes are used to test the accuracy rate of the method. The accuracy rate is more than 90%. The experimental results demonstrate that the novel method can detect oil spills validly and accurately.
基金Sponsored by the National Natural Science Foundation of China(60890071-1160890071-0760890073)
文摘Global navigation satellite system（GNSS） can be employed as a transmitter to composite bistatic synthetic aperture radar（BiSAR）.As GNSS signal is quite different from the traditional radar signal,modified spectral analysis（SPECAN） algorithm is proposed and applied in the BiSAR system.The modifications include Doppler centroid compensation,range curve correction and azimuth processing method.The modified SPECAN algorithm solves the imaging problem under the condition of huge range migration,long synthetic aperture time and phase-coded signal.The proposed algorithm is verified by experiment results.
