In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quali...In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.展开更多
The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the pre...The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.展开更多
This paper describes a method for building hot snapshot copy based on windows-file system （HSCF）. The architecture and running mechanism of HSCF are discussed after giving a comparison with other on-line backup tecb...This paper describes a method for building hot snapshot copy based on windows-file system （HSCF）. The architecture and running mechanism of HSCF are discussed after giving a comparison with other on-line backup tecbnology. HSCF, based on a file system filter driver, protects computer data and ensures their integrity and consistency with following three steps： access to open files, synchronization and copy on-write. Its strategies for improving system performance are analyzed including priority setting, incremental snapshot and load balance. HSCF is a new kind of snapshot technology to solve the data integrity and consistency problem in online backup, which is different from other storage-level snapshot and Open File Solution.展开更多
The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andf...The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.展开更多
Adaptive digital filtering has traditionally been developed based on the minimum mean square error （MMSE） criterion and has found ever-increasing applications in communications. This paper presents an alternative ad...Adaptive digital filtering has traditionally been developed based on the minimum mean square error （MMSE） criterion and has found ever-increasing applications in communications. This paper presents an alternative adaptive filtering design based on the minimum symbol error rate （MSER） criterion for communication applications. It is shown that the MSER filtering is smarter, as it exploits the non-Gaussian distribution of filter output effectively. Consequently, it provides significant performance gain in terms of smaller symbol error over the MMSE approach. Adopting Parzen window or kernel density estimation for a probability density function, a block-data gradient adaptive MSER algorithm is derived. A stochastic gradient adaptive MSER algorithm, referred to as the least symbol error rate, is further developed for sample-by-sample adaptive implementation of the MSER filtering. Two applications, involving single-user channel equalization and beamforming assisted receiver, are included to demonstrate the effectiveness and generality of the proposed adaptive MSER filtering approach.展开更多
Interferometric phase filtering is one of the key steps in interferometricsynthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult toobtain due to dense fringe and low coherence regions...Interferometric phase filtering is one of the key steps in interferometricsynthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult toobtain due to dense fringe and low coherence regions. Moreover, the InSAR/SAR datarange is relatively large, so the efficiency of interferential phase filtering is one of themajor problems. In this letter, we proposed an interferometric phase filtering methodbased on an amended matrix pencil and linear window mean filter. The combination ofthe matrix pencil and the linear mean filter are introduced to the interferometric phasefiltering for the first time. First, the interferometric signal is analyzed, and theinterferometric phase filtering is transformed into a local frequency estimation problem.Then, the local frequency is estimated using an amended matrix pencil at a window. Thelocal frequency can represent terrain changes, thus suggesting that the frequency can beaccurately estimated even in dense fringe regions. Finally, the local frequency is filteredby using a linear window mean filter, and the filtered phase is recovered. The proposedmethod is calculated by some matrices. Therefore, the computational complexity isreduced, and the efficiency of the interferometric phase filtering is improved.Experiments are conducted with simulated and real InSAR data. The proposed methodexhibits a better filtering effect and an ideal efficiency as compared with the traditionalfiltering method.展开更多
A scheme for designing one-dimensional (1-D) convolution window of the circularly symmetric Gabor filter which is directly obtained from frequency domain is proposed. This scheme avoids the problem of choosing the sam...A scheme for designing one-dimensional (1-D) convolution window of the circularly symmetric Gabor filter which is directly obtained from frequency domain is proposed. This scheme avoids the problem of choosing the sampling frequency in the spatial domain, or the sampling frequency must be determined when the window data is obtained by means of sampling the Gabor function, the impulse response of the Gabor filter. In this scheme, the discrete Fourier transform of the Gabor function is obtained by discretizing its Fourier transform. The window data can be derived by minimizing the sums of the squares of the complex magnitudes of difference between its discrete Fourier transform and the Gabor function's discrete Fourier transform. Not only the full description of this scheme but also its application to fabric defect detection are given in this paper. Experimental results show that the 1-D convolution windows can be used to significantly reduce computational cost and greatly ensure the quality of the Gabor filters. So this scheme can be used in some real-time processing systems.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.62201051,62101039)in part by the Shandong Excellent Young Scientists Fund Program(Overseas)in part by the National Key Research and Development Program of China(No.SQ2022YFB3900055).
文摘In order to mitigate speckle noise in synthetic aperture radar(SAR)images and enhance the accuracy of SAR tomography,non-local means(NL-means)filtering has been proven to be an effective method for improving the quality of SAR interferograms.Apart from considerations like noise type and the definition of similarity,the size and shape of filtering windows are critical factors influencing the efficacy of NL-means filtering,yet there has been limited research on this aspect.This paper introduces an enhanced NL-means filtering method based on adaptive windows,allowing for the automatic adjustment of filtering window size according to the amplitude information of the SAR interferogram.Simultaneously,a directional window is incorporated to align SAR interferograms,achieving the dual objective of preserving filtering standards and retaining detailed information.Experimental results on interferogram filtering and tomography,based on TerraSAR-X data,demonstrate that the proposed method effectively reduces phase noise while maintaining texture accuracy,thereby improving tomography quality.
基金support of the National Natural Science Fundation of China (Nos. 41574105 and 41674118)the National Science and Technology Major Project of China (No. 2016ZX05027-002)the Scientific and Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology (No. 2015ASKJ03)
文摘The surface-related multiple elimination(SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas.
基金Supported by the National Natural Science Foun-dation of China (60473023) National Innovation Foundation forSmall Technology Based Firms(04C26214201280)
文摘This paper describes a method for building hot snapshot copy based on windows-file system （HSCF）. The architecture and running mechanism of HSCF are discussed after giving a comparison with other on-line backup tecbnology. HSCF, based on a file system filter driver, protects computer data and ensures their integrity and consistency with following three steps： access to open files, synchronization and copy on-write. Its strategies for improving system performance are analyzed including priority setting, incremental snapshot and load balance. HSCF is a new kind of snapshot technology to solve the data integrity and consistency problem in online backup, which is different from other storage-level snapshot and Open File Solution.
基金Project(51675262)supported by the National Natural Science Foundation of ChinaProject(6140210020102)supported by the Advance Research Field Fund Project of ChinaProject(2016YFD0700800)supported by the National Key Research and Development Plan of China
文摘The goal of this paper is to find an excellent adaptive window function for extracting the weak vibration signal and high frequency vibration signal under strong noise.The relationship between windowing transform andfiltering is analyzed first in the paper.The advantage of adjustable time-frequency window of wavelet transform is introduced.Secondly the relationship between harmonic wavelet and multiple analytic band-pass filter is analyzed.The coherence of the multiple analytic band-pass filter and harmonic wavelet base function is discussed,and the characteristic that multiple analytic band-pass filter included in the harmonic wavelet transform is founded.Thirdly,by extending the harmonic wavelet transform,the concept of the adaptive harmonic window and its theoretical equation without decomposition are put forward in this paper.Then comparing with the Hanning window,the good performance of restraining side-lobe leakage possessed by adaptive harmonic window is shown,and the adaptive characteristics of window width changing and analytical center moving of the adaptive harmonic window are presented.Finally,the proposed adaptive harmonic window is applied to weak signal extraction and high frequency orbit extraction of high speed rotor under strong noise,and the satisfactory results are achieved.The application results show that the adaptive harmonic window function can be successfully applied to the actual engineering signal processing.
文摘Adaptive digital filtering has traditionally been developed based on the minimum mean square error （MMSE） criterion and has found ever-increasing applications in communications. This paper presents an alternative adaptive filtering design based on the minimum symbol error rate （MSER） criterion for communication applications. It is shown that the MSER filtering is smarter, as it exploits the non-Gaussian distribution of filter output effectively. Consequently, it provides significant performance gain in terms of smaller symbol error over the MMSE approach. Adopting Parzen window or kernel density estimation for a probability density function, a block-data gradient adaptive MSER algorithm is derived. A stochastic gradient adaptive MSER algorithm, referred to as the least symbol error rate, is further developed for sample-by-sample adaptive implementation of the MSER filtering. Two applications, involving single-user channel equalization and beamforming assisted receiver, are included to demonstrate the effectiveness and generality of the proposed adaptive MSER filtering approach.
基金The authors would like to thank the support by the State Key Program of National Natural Science Foundation of China under Grant[Number 41774026]the Satellite Mapping Technology and Application,National Administration of Surveying,Mapping and Geoinformation Key Laboratory under Grant[Number KLSMTA-201708].
文摘Interferometric phase filtering is one of the key steps in interferometricsynthetic aperture radar (InSAR/SAR). However, the ideal filtering results are difficult toobtain due to dense fringe and low coherence regions. Moreover, the InSAR/SAR datarange is relatively large, so the efficiency of interferential phase filtering is one of themajor problems. In this letter, we proposed an interferometric phase filtering methodbased on an amended matrix pencil and linear window mean filter. The combination ofthe matrix pencil and the linear mean filter are introduced to the interferometric phasefiltering for the first time. First, the interferometric signal is analyzed, and theinterferometric phase filtering is transformed into a local frequency estimation problem.Then, the local frequency is estimated using an amended matrix pencil at a window. Thelocal frequency can represent terrain changes, thus suggesting that the frequency can beaccurately estimated even in dense fringe regions. Finally, the local frequency is filteredby using a linear window mean filter, and the filtered phase is recovered. The proposedmethod is calculated by some matrices. Therefore, the computational complexity isreduced, and the efficiency of the interferometric phase filtering is improved.Experiments are conducted with simulated and real InSAR data. The proposed methodexhibits a better filtering effect and an ideal efficiency as compared with the traditionalfiltering method.
基金Scientific and Technological Development Project of Beijing Municipal Education Commission (No KM200510012002)
文摘A scheme for designing one-dimensional (1-D) convolution window of the circularly symmetric Gabor filter which is directly obtained from frequency domain is proposed. This scheme avoids the problem of choosing the sampling frequency in the spatial domain, or the sampling frequency must be determined when the window data is obtained by means of sampling the Gabor function, the impulse response of the Gabor filter. In this scheme, the discrete Fourier transform of the Gabor function is obtained by discretizing its Fourier transform. The window data can be derived by minimizing the sums of the squares of the complex magnitudes of difference between its discrete Fourier transform and the Gabor function's discrete Fourier transform. Not only the full description of this scheme but also its application to fabric defect detection are given in this paper. Experimental results show that the 1-D convolution windows can be used to significantly reduce computational cost and greatly ensure the quality of the Gabor filters. So this scheme can be used in some real-time processing systems.
