A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW...A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW)approach for homogeneous dielectric objects and the electric field integral equation for conducting objects.The integral equations are discretized by the method of moment(MoM),in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions.The resultant matrix equation is then solved by the multilevel fast multipole algorithm(MLFMA)and fast far-field approximation(FAFFA)is used to further accelerate the computation.The radiation patterns of dipole arrays in the presence of radomes are presented.The numerical results demonstrate the accuracy and versatility of this method.展开更多
Image matching refers to the process of matching two or more images obtained at different time,different sensors or different conditions through a large number of feature points in the image.At present,image matching ...Image matching refers to the process of matching two or more images obtained at different time,different sensors or different conditions through a large number of feature points in the image.At present,image matching is widely used in target recognition and tracking,indoor positioning and navigation.Local features missing,however,often occurs in color images taken in dark light,making the extracted feature points greatly reduced in number,so as to affect image matching and even fail the target recognition.An unsharp masking(USM)based denoising model is established and a local adaptive enhancement algorithm is proposed to achieve feature point compensation by strengthening local features of the dark image in order to increase amount of image information effectively.Fast library for approximate nearest neighbors(FLANN)and random sample consensus(RANSAC)are image matching algorithms.Experimental results show that the number of effective feature points obtained by the proposed algorithm from images in dark light environment is increased,and the accuracy of image matching can be improved obviously.展开更多
基金the National Natural Science Foundation of China(60431010)
文摘A full-wave analysis of the electromagnetic problem of a three-dimensional(3-D)antenna radiating through a 3-D dielectric radome is preserued.The problem is formulated using the Poggio-Miller-Chang-Harrington-Wu(PMCHW)approach for homogeneous dielectric objects and the electric field integral equation for conducting objects.The integral equations are discretized by the method of moment(MoM),in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions.The resultant matrix equation is then solved by the multilevel fast multipole algorithm(MLFMA)and fast far-field approximation(FAFFA)is used to further accelerate the computation.The radiation patterns of dipole arrays in the presence of radomes are presented.The numerical results demonstrate the accuracy and versatility of this method.
基金Supported by the National Natural Science Foundation of China(No.61771186)the Heilongjiang Provincial Natural Science Foundation of China(No.YQ2020F012)the University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(No.UNPYSCT-2017125).
文摘Image matching refers to the process of matching two or more images obtained at different time,different sensors or different conditions through a large number of feature points in the image.At present,image matching is widely used in target recognition and tracking,indoor positioning and navigation.Local features missing,however,often occurs in color images taken in dark light,making the extracted feature points greatly reduced in number,so as to affect image matching and even fail the target recognition.An unsharp masking(USM)based denoising model is established and a local adaptive enhancement algorithm is proposed to achieve feature point compensation by strengthening local features of the dark image in order to increase amount of image information effectively.Fast library for approximate nearest neighbors(FLANN)and random sample consensus(RANSAC)are image matching algorithms.Experimental results show that the number of effective feature points obtained by the proposed algorithm from images in dark light environment is increased,and the accuracy of image matching can be improved obviously.
