The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is pro...The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.展开更多
A new technique is proposed for range alignment in Inverse Synthetic Aperture Radar （ISAR）. The basic idea is to perform range alignment using a maximum kurtosis （fourth-order central moment） criterion. After maxi...A new technique is proposed for range alignment in Inverse Synthetic Aperture Radar （ISAR）. The basic idea is to perform range alignment using a maximum kurtosis （fourth-order central moment） criterion. After maximizing the kurtosis of the combined range profile of two adjacent echoes, the amount of range shift between them can be automatically tracked out. The combined range profile is constructed by a max operation, which only reserves the larger elements of the two echoes, and the echoes＇ amplitudes are limited before they are combined. This algorithm has bee~ used to process real ISAR data and the results demonstrate the effectiveness of the method. Compared with the correlation method and the minimum entropy method, the proposed algorithm obtains much better results in both examples in this paper. Its computation complexity has the same order of magnitude as the minimum entropy method.展开更多
In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infini...In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infinity) w(i)S(w)dw. Glazman's partial averaging idea is discussed. It is pointed out that Glazman's method and definition of non-dimensional spectral moment can not be used to estimate spectral moments for engineering purposes and that method is not supported by theory and computation. The non-dimensional spectral moment of PM spectrum, which should be expressed as [GRAPHICS] is related to wind speed. The 0 - 8th moments of PM spectrum are estimated for wind speeds of 10, 20 and 30 m/s and some discussions are given.展开更多
文摘The paper addresses the problem of target recognition using High-resolution Radar Range Profiles(HRRP).A novel approach of feature extraction and dimension reduction based on extended high order central moments is proposed in order to reduce the dimension of range profiles.Features extracted from radar HRRPs are normalized and smoothed,and then comparative analysis of the similar approaches is done.The range profiles are obtained by step frequency technique using the two-dimensional backscatters distribution data of four different aircraft models.The template matching method by nearest neighbor rules,which is based on the theory of kernel methods for pattern analysis,is used to classify and identify the range profiles from four different aircrafts.Numerical simulation results show that the proposed approach can achieve good performance of stability,shift independence and higher recognition rate.It is helpful for real-time identification and the engineering implements of automatic target recognition using HRRP.The number of required templates could be reduced con-siderably while maintaining an equivalent recognition rate.
基金the National Natural Science Foundation of China (No.60502030) and Aeronautical Science Founda-tion of China (No.05D52027).
文摘A new technique is proposed for range alignment in Inverse Synthetic Aperture Radar （ISAR）. The basic idea is to perform range alignment using a maximum kurtosis （fourth-order central moment） criterion. After maximizing the kurtosis of the combined range profile of two adjacent echoes, the amount of range shift between them can be automatically tracked out. The combined range profile is constructed by a max operation, which only reserves the larger elements of the two echoes, and the echoes＇ amplitudes are limited before they are combined. This algorithm has bee~ used to process real ISAR data and the results demonstrate the effectiveness of the method. Compared with the correlation method and the minimum entropy method, the proposed algorithm obtains much better results in both examples in this paper. Its computation complexity has the same order of magnitude as the minimum entropy method.
基金This work was financially supported by the National Natural Science Foundation of China(Grant No.49776282)
文摘In order to obtain high order spectral moments, the residual moment M(w(n))(i) = integral(0)(wn) w(i)S(w)dw, as proposed by Denis s, is presented for approximate estimation of spectral moment m(i) = integral(0)(infinity) w(i)S(w)dw. Glazman's partial averaging idea is discussed. It is pointed out that Glazman's method and definition of non-dimensional spectral moment can not be used to estimate spectral moments for engineering purposes and that method is not supported by theory and computation. The non-dimensional spectral moment of PM spectrum, which should be expressed as [GRAPHICS] is related to wind speed. The 0 - 8th moments of PM spectrum are estimated for wind speeds of 10, 20 and 30 m/s and some discussions are given.
