As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A ph...As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.展开更多
To better retain useful weak low-frequency magnetotelluric(MT)signals with strong interference during MT data processing,we propose a SVM-CEEMDWT based MT data signal-noise separation method,which extracts the weak MT...To better retain useful weak low-frequency magnetotelluric(MT)signals with strong interference during MT data processing,we propose a SVM-CEEMDWT based MT data signal-noise separation method,which extracts the weak MT signal affected by strong interference.First,the approximate entropy,fuzzy entropy,sample entropy,and Lempel-Ziv(LZ)complexity are extracted from the magnetotelluric data.Then,four robust parameters are used as the inputs to the support vector machine(SVM)to train the sample library and build a model based on the different complexity of signals.Based on this model,we can only consider time series with strong interference when using the complementary ensemble empirical mode decomposition(CEEMD)and wavelet threshold(WT)for noise suppression.Simulation results suggest that the SVM based on the robust parameters can distinguish the time periods with strong interference well before noise suppression.Compared with the CEEMD WT,the proposed SVM-CEEMDWT method retains more low-frequency low-variability information,and the apparent resistivity curve is smoother and more continuous.Moreover,the results better reflect the deep electrical structure in the field.展开更多
When the five-axis CNC system executes the 3D cutter radius compensation function,the angle between two adjacent radius compensation vectors might become very large and the linear axes would move too fast if the tool ...When the five-axis CNC system executes the 3D cutter radius compensation function,the angle between two adjacent radius compensation vectors might become very large and the linear axes would move too fast if the tool orientation vector is close to the surface normal.The reason that results in this phenomenon is analyzed based on building the transmission relationship between the cutter contact point and the cutter location point.By taking the square-end tool as an example,an optimization algorithm to control the undesired movements is advanced.For the singular area where sudden change exists,the number of interpolation cycles is determined by the cutter feedrate,the limit speeds of machine axes and the maximum allowable angle between radius compensation vectors of adjacent NC blocks.The radius compensation vector of each interpolation cycle is obtained by a kind of vector rotation method.By maintaining the perpendicularity between the radius compensation vector and the tool orientation vector,the rapid movements of the linear axes are eliminated.A trial-cut experiment is performed to verify the correctness and the effectiveness of the proposed algorithm.展开更多
基金Supported by the National Natural Science Foundation of China(61071165)the Program for NewCentury Excellent Talents in University(NCET-09-0069)the Defense Industrial Technology Development Program(B2520110008)~~
文摘As same as the conventional inverse synthetic aperture radar（ISAR）, the compressed ISAR also requires the echo signal based motion compensation, which consists of the range alignment and the phase autofoeusing. A phase autofocusing algorithm for compressed ISAR imaging is presented. In the algorithm, phase autofocusing for the sparse ISAR echoes is accomplished using the eigenvector method. Experimental results validate the effectiveness of the algorithm.
基金funded by the National Key R&D Program of China(No.2018YFC0603202)the National Natural Science Foundation of China(No.41404111)+1 种基金Natural Science Foundation of Hunan Province(No.2018JJ2258)Hunan Provincial Science and Technology Project Foundation(No.2018TP1018)
文摘To better retain useful weak low-frequency magnetotelluric(MT)signals with strong interference during MT data processing,we propose a SVM-CEEMDWT based MT data signal-noise separation method,which extracts the weak MT signal affected by strong interference.First,the approximate entropy,fuzzy entropy,sample entropy,and Lempel-Ziv(LZ)complexity are extracted from the magnetotelluric data.Then,four robust parameters are used as the inputs to the support vector machine(SVM)to train the sample library and build a model based on the different complexity of signals.Based on this model,we can only consider time series with strong interference when using the complementary ensemble empirical mode decomposition(CEEMD)and wavelet threshold(WT)for noise suppression.Simulation results suggest that the SVM based on the robust parameters can distinguish the time periods with strong interference well before noise suppression.Compared with the CEEMD WT,the proposed SVM-CEEMDWT method retains more low-frequency low-variability information,and the apparent resistivity curve is smoother and more continuous.Moreover,the results better reflect the deep electrical structure in the field.
基金supported by the National Basic Research Program of China under Grant No.2011CB302400the National Key Technology Research and Development Program of China under Grant No.2012BAF13B08
文摘When the five-axis CNC system executes the 3D cutter radius compensation function,the angle between two adjacent radius compensation vectors might become very large and the linear axes would move too fast if the tool orientation vector is close to the surface normal.The reason that results in this phenomenon is analyzed based on building the transmission relationship between the cutter contact point and the cutter location point.By taking the square-end tool as an example,an optimization algorithm to control the undesired movements is advanced.For the singular area where sudden change exists,the number of interpolation cycles is determined by the cutter feedrate,the limit speeds of machine axes and the maximum allowable angle between radius compensation vectors of adjacent NC blocks.The radius compensation vector of each interpolation cycle is obtained by a kind of vector rotation method.By maintaining the perpendicularity between the radius compensation vector and the tool orientation vector,the rapid movements of the linear axes are eliminated.A trial-cut experiment is performed to verify the correctness and the effectiveness of the proposed algorithm.
