The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the...The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the circular scanning synthetic aperture radar(SAR) has been applied to wide surveillance of the sea surface.Therefore, the paper analyzes the validity of available sea clutter models for range Doppler images from different scan angles for moderate sea state in the medium grazing angle. The parameter estimation method for different distribution models employs the method of logarithmic cumulant(MoLC) based on Mellin transform uniformly. By the analysis of the fitting performance between the histogram of real data and the amplitude probability density function(PDF) of empirical distribution models and the goodness-of-fit(GoF) test for real data from different scan angles, it is indicated the generalized K(GK) distribution with generalized Gamma texture distribution can fit the sea clutter well for different scan angles in the medium grazing angle.展开更多
The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the syn...The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.展开更多
基金supported by the National Natural Science Foundation of China(61621005 61671352)+2 种基金the Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education(Guilin University of Electronic Technology)(CRKL160206)the Innovational Foundation of Shanghai Academy of Space Technology(SAST2016027SAST2016033)
文摘The theoretical statistical model of sea clutter is a key issue for maritime surveillance. In recent years, the statistical model of sea clutter has attracted much attention to design the detector well. Meanwhile, the circular scanning synthetic aperture radar(SAR) has been applied to wide surveillance of the sea surface.Therefore, the paper analyzes the validity of available sea clutter models for range Doppler images from different scan angles for moderate sea state in the medium grazing angle. The parameter estimation method for different distribution models employs the method of logarithmic cumulant(MoLC) based on Mellin transform uniformly. By the analysis of the fitting performance between the histogram of real data and the amplitude probability density function(PDF) of empirical distribution models and the goodness-of-fit(GoF) test for real data from different scan angles, it is indicated the generalized K(GK) distribution with generalized Gamma texture distribution can fit the sea clutter well for different scan angles in the medium grazing angle.
基金Project(61105020)supported by the National Natural Science Foundation of ChinaProject(13zxtk08)supported by the Key Research Platform for Research Projects of Southwest University of Science and Technology,China
文摘The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.
