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2015 Vol. 37, No. 2
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2015, 37(2): 255-260.
doi: 10.11999/JEIT140451
Abstract:
Aiming at the problem that the maximum Error Controllable compression based on SVD (EC-SVD) algorithm can not make full use of spectral vectors redundancy in hyperspectral image, a hyperspectral image compression algorithm with maximum error controlled based on clustering is presented in this paper, by combining hyperspectral image compression with clustering. It is found that a higher compression ratio can be achieved as spectral vectors similarity increases. Using the K-means clustering algorithm, the pixels of hyperspectral image are clustered by spectral vectors to improve the similarity of spectral vectors in the same class. Then, the pixels in each class are compressed using the idea of EC-SVD algorithm. And it is shown that the compression ratio increases if the cluster number is no more than 8 and the number of pixels is larger than that of bands in the clustered hyperspectral image. Finally, a total simulation procedure of the improved compression algorithm is designed and some hyperspectral images are tested. The results of the tests show that compression ratios and signal to noise ratios are higher than those of EC-SVD algorithm under the same parameters; the maximum compression ratio rises around 10 percent. The presented improved algorithm can raise the compression efficiencies of hyperspectral images.
Aiming at the problem that the maximum Error Controllable compression based on SVD (EC-SVD) algorithm can not make full use of spectral vectors redundancy in hyperspectral image, a hyperspectral image compression algorithm with maximum error controlled based on clustering is presented in this paper, by combining hyperspectral image compression with clustering. It is found that a higher compression ratio can be achieved as spectral vectors similarity increases. Using the K-means clustering algorithm, the pixels of hyperspectral image are clustered by spectral vectors to improve the similarity of spectral vectors in the same class. Then, the pixels in each class are compressed using the idea of EC-SVD algorithm. And it is shown that the compression ratio increases if the cluster number is no more than 8 and the number of pixels is larger than that of bands in the clustered hyperspectral image. Finally, a total simulation procedure of the improved compression algorithm is designed and some hyperspectral images are tested. The results of the tests show that compression ratios and signal to noise ratios are higher than those of EC-SVD algorithm under the same parameters; the maximum compression ratio rises around 10 percent. The presented improved algorithm can raise the compression efficiencies of hyperspectral images.
2015, 37(2): 261-267.
doi: 10.11999/JEIT140331
Abstract:
A new SAR image segmentation model with edge penalty is constructed, which uses oriented edge strength information and a minimized hierarchical region merging algorithm is proposed in this paper. The edge strength information is extracted by using Multi-Direction Ratio Edge Detector (MDRED), based on which a high quality initial over-segmentation is obtained using watershed transformation. In order to extract the directions of boundaries of regions, polygons are used to approximate them, and a penalty term whose power is in inverse proportion to edge strength is obtained by incorporating Oriented Edge Strength Map (OESM) into the term. A hierarchical region merging algorithm driven by image features is obtained through graduated increased edge penalty. In order to accelerate the region merging, the Region Adjacency Graph (RAG) is used to represent the image segmentation. The experimental results show that the proposed method has advantages in performance and efficiency, and obtains better segmentation results with respect to other methods.
A new SAR image segmentation model with edge penalty is constructed, which uses oriented edge strength information and a minimized hierarchical region merging algorithm is proposed in this paper. The edge strength information is extracted by using Multi-Direction Ratio Edge Detector (MDRED), based on which a high quality initial over-segmentation is obtained using watershed transformation. In order to extract the directions of boundaries of regions, polygons are used to approximate them, and a penalty term whose power is in inverse proportion to edge strength is obtained by incorporating Oriented Edge Strength Map (OESM) into the term. A hierarchical region merging algorithm driven by image features is obtained through graduated increased edge penalty. In order to accelerate the region merging, the Region Adjacency Graph (RAG) is used to represent the image segmentation. The experimental results show that the proposed method has advantages in performance and efficiency, and obtains better segmentation results with respect to other methods.
2015, 37(2): 268-275.
doi: 10.11999/JEIT140199
Abstract:
A Structure Preserving Bilateral Filtering (SPBF) is proposed to address the problem of preserving structural information for reducing speckle in a PolSAR image. The edge structural characteristics and surface scattering features are adopted to measure structural information in PolSAR image, which can reduce loss of structure and improve filtering performance. To begin with, the edge direction is determined by edge templates, and then an adaptive direction window is selected in span image. Furthermore, each scattering mechanism of the pixel is obtained by Freeman-Durden decomposition. And then surface scattering map is obtained by statistical distribution characteristics of polarimetric data. Finally, the filtering mask, which combines the cluster map with adapted direction window, is introduced into an improved bilateral filtering. The experimental results of real SAR images show that the proposed method can efficiently reduce speckle, and further preserve image edge, the strong point target and polarimetric scattering characteristics.
A Structure Preserving Bilateral Filtering (SPBF) is proposed to address the problem of preserving structural information for reducing speckle in a PolSAR image. The edge structural characteristics and surface scattering features are adopted to measure structural information in PolSAR image, which can reduce loss of structure and improve filtering performance. To begin with, the edge direction is determined by edge templates, and then an adaptive direction window is selected in span image. Furthermore, each scattering mechanism of the pixel is obtained by Freeman-Durden decomposition. And then surface scattering map is obtained by statistical distribution characteristics of polarimetric data. Finally, the filtering mask, which combines the cluster map with adapted direction window, is introduced into an improved bilateral filtering. The experimental results of real SAR images show that the proposed method can efficiently reduce speckle, and further preserve image edge, the strong point target and polarimetric scattering characteristics.
2015, 37(2): 276-282.
doi: 10.11999/JEIT140146
Abstract:
The active repeater jamming is a very important jamming technique in the modern warfare, especially for the air defense, anti-missile and anti-warship operations. It becomes a serious threat for the modern radar systems. This paper focuses on the representative distance-deception and angle-deception artifacts in radar formed by the active repeater jamming techniques. The discrimination and suppression of such active repeater jamming with fully polarimetric mono-pulse radar is studied. The theoretical investigations and simulation experiments demonstrate and validate that the utilization of polarization information has the capability to identify and suppress these jamming patterns. The obtained conclusion shows great potential for the further studies and can assist the investigation of the issue that how radar can be adapted to the complex electromagnetic environment.
The active repeater jamming is a very important jamming technique in the modern warfare, especially for the air defense, anti-missile and anti-warship operations. It becomes a serious threat for the modern radar systems. This paper focuses on the representative distance-deception and angle-deception artifacts in radar formed by the active repeater jamming techniques. The discrimination and suppression of such active repeater jamming with fully polarimetric mono-pulse radar is studied. The theoretical investigations and simulation experiments demonstrate and validate that the utilization of polarization information has the capability to identify and suppress these jamming patterns. The obtained conclusion shows great potential for the further studies and can assist the investigation of the issue that how radar can be adapted to the complex electromagnetic environment.
2015, 37(2): 283-290.
doi: 10.11999/JEIT140261
Abstract:
Forest parameters inversion is an important application of Polarimetric Interference Synthetic Aperture Radar (PolInSAR). The traditional inversion method does not take into account the amplitude and phase non-stationary of observation, and its non-uniform distribution effect on the estimation of the principal linear change direction. Aiming at these problems, an amplitude and phase calibration approach is proposed to compensate the polarization coherence matrix nonstationarity, to enhance the performance of complex coherences estimation. Moreover, this paper develops a Mapping Space Regularization (MSR) technology which promises to be able to eliminate the non-uniform distribution effect of sample coherences on the linear variation of complex coherences. Based on MSR, the Principal Component Analysis (PCA) is further introduced to the linear variation model extraction. Processing results of ESA PolSARpro simulated data verify the better robustness and estimation accuracy of the proposal in forest parameters inversion.
Forest parameters inversion is an important application of Polarimetric Interference Synthetic Aperture Radar (PolInSAR). The traditional inversion method does not take into account the amplitude and phase non-stationary of observation, and its non-uniform distribution effect on the estimation of the principal linear change direction. Aiming at these problems, an amplitude and phase calibration approach is proposed to compensate the polarization coherence matrix nonstationarity, to enhance the performance of complex coherences estimation. Moreover, this paper develops a Mapping Space Regularization (MSR) technology which promises to be able to eliminate the non-uniform distribution effect of sample coherences on the linear variation of complex coherences. Based on MSR, the Principal Component Analysis (PCA) is further introduced to the linear variation model extraction. Processing results of ESA PolSARpro simulated data verify the better robustness and estimation accuracy of the proposal in forest parameters inversion.
2015, 37(2): 291-296.
doi: 10.11999/JEIT140494
Abstract:
Time-frequency image of multi-ballistic targets is composed of micro-Doppler of multi-targets with multi-scattering centers, which makes the methods for single target invalid. Firstly, micro-Doppler of precessing missile and swinging decoy is analyzed. Considering midcourse ballistic targets characteristics that the motion is stable and the acceleration is approximately a constant in short time, Radon transform is applied to the detection of linear degree of the micro-Doppler, then motional parameters are estimated based on minimum entropy criteria and Gauss fitting. After compensating translation, Viterbi algorithm is used to extract micro-Doppler from the time-frequency image, with which multi-targets can be resolved according to the principle that scattering centers on one target are with the same micro-Doppler cycles, but those on different targets are not. Finally, Simulations verify the effectiveness of the proposed method.
Time-frequency image of multi-ballistic targets is composed of micro-Doppler of multi-targets with multi-scattering centers, which makes the methods for single target invalid. Firstly, micro-Doppler of precessing missile and swinging decoy is analyzed. Considering midcourse ballistic targets characteristics that the motion is stable and the acceleration is approximately a constant in short time, Radon transform is applied to the detection of linear degree of the micro-Doppler, then motional parameters are estimated based on minimum entropy criteria and Gauss fitting. After compensating translation, Viterbi algorithm is used to extract micro-Doppler from the time-frequency image, with which multi-targets can be resolved according to the principle that scattering centers on one target are with the same micro-Doppler cycles, but those on different targets are not. Finally, Simulations verify the effectiveness of the proposed method.
2015, 37(2): 297-302.
doi: 10.11999/JEIT140535
Abstract:
Microwave 3-D imaging technique can accurately separate and extract the attractive targets from the background noise. So it can be utilized to analyze and study the ElectroMagnetic (EM) scattering characteristics of the outfield targets. Thus researching the EM scattering characteristics of targets from the perspective of 3-D SAR imaging is becoming an emerging hot field. Based on the background above, firstly, the near field 3-D imaging process in wave-number domain is deduced from the Stratton-Chu integral equation and the physical meaning of 3-D SAR imaging is explained. Then, the principle of targets Radar Cross Section (RCS) Near-Field-to-Far-Field Transformation (NFFFT) based on 3-D SAR imaging is elaborated and the method of scattering center extraction from 3-D SAR image is introduced and the algorithm of targets RCS NFFFT based on 3-D SAR imaging technique is presented. Finally, though some experiments using the FEKO software, five scattering points observing angle characteristic curve and frequency characteristic curve are gotten. Through the comparative experiments with the ideal situation, the effectiveness of the RCS NFFFT algorithm is validated.
Microwave 3-D imaging technique can accurately separate and extract the attractive targets from the background noise. So it can be utilized to analyze and study the ElectroMagnetic (EM) scattering characteristics of the outfield targets. Thus researching the EM scattering characteristics of targets from the perspective of 3-D SAR imaging is becoming an emerging hot field. Based on the background above, firstly, the near field 3-D imaging process in wave-number domain is deduced from the Stratton-Chu integral equation and the physical meaning of 3-D SAR imaging is explained. Then, the principle of targets Radar Cross Section (RCS) Near-Field-to-Far-Field Transformation (NFFFT) based on 3-D SAR imaging is elaborated and the method of scattering center extraction from 3-D SAR image is introduced and the algorithm of targets RCS NFFFT based on 3-D SAR imaging technique is presented. Finally, though some experiments using the FEKO software, five scattering points observing angle characteristic curve and frequency characteristic curve are gotten. Through the comparative experiments with the ideal situation, the effectiveness of the RCS NFFFT algorithm is validated.
2015, 37(2): 303-308.
doi: 10.11999/JEIT140564
Abstract:
For broadside spotlight Synthetic Aperture Radar (SAR) imaging, Polar Format Algorithm (PFA) is applied widely as a kind of general interpolation algorithm. When PFA is applied to the squinted spotlight, coordinate rotation causes azimuth spectrum uniformly resampled. A new method of interpolation for azimuth spectrum is proposed in this paper and the accurate form of azimuth spectrum interpolation is given according to the geometry of squinted spotlight. Azimuth spectrum is resampled according to the accurate form of interpolation and uniform azimuth spectrum is obtained. Then, two-dimension IFFT is implemented and high resolution squinted spotlight image is obtained. In order to validate the effectiveness, simulation and real data are processed by the proposed method. Compared with traditional interpolation method, the scope of well-focused image is increased.
For broadside spotlight Synthetic Aperture Radar (SAR) imaging, Polar Format Algorithm (PFA) is applied widely as a kind of general interpolation algorithm. When PFA is applied to the squinted spotlight, coordinate rotation causes azimuth spectrum uniformly resampled. A new method of interpolation for azimuth spectrum is proposed in this paper and the accurate form of azimuth spectrum interpolation is given according to the geometry of squinted spotlight. Azimuth spectrum is resampled according to the accurate form of interpolation and uniform azimuth spectrum is obtained. Then, two-dimension IFFT is implemented and high resolution squinted spotlight image is obtained. In order to validate the effectiveness, simulation and real data are processed by the proposed method. Compared with traditional interpolation method, the scope of well-focused image is increased.
2015, 37(2): 309-314.
doi: 10.11999/JEIT140529
Abstract:
In view of the uneven imaging data caused by the uneven space-time array in the MIMO-ISAR imaging, the echo signal model of a target is established based on a linear array, an imaging algorithm that focuses on the cross-range direction following range unit is proposed. The range compensation is applied firstly, which can make range profiles that distribute in the space-time domain align at the initial position of target. Then phase changes caused by motion in unconcerned direction are compensated. Finally, the range profiles are focused in the cross-range direction following range unit by coherent addition. The algorithm is not restricted by the structure of the array and the processing of uniformity is not needed. In addition, it can determine the ISAR image scale in the cross-range direction. The simulation results verify the validity of the proposed algorithm.
In view of the uneven imaging data caused by the uneven space-time array in the MIMO-ISAR imaging, the echo signal model of a target is established based on a linear array, an imaging algorithm that focuses on the cross-range direction following range unit is proposed. The range compensation is applied firstly, which can make range profiles that distribute in the space-time domain align at the initial position of target. Then phase changes caused by motion in unconcerned direction are compensated. Finally, the range profiles are focused in the cross-range direction following range unit by coherent addition. The algorithm is not restricted by the structure of the array and the processing of uniformity is not needed. In addition, it can determine the ISAR image scale in the cross-range direction. The simulation results verify the validity of the proposed algorithm.
2015, 37(2): 315-321.
doi: 10.11999/JEIT140407
Abstract:
It usually takes a long observing time when a cognitive radar transmits the High-Range-Resolution (HRR) stepped-frequency signal. To save time, partial pulses of the stepped-frequency signal are transmitted to obtain the incomplete frequency data, and a Bayesian reconstruction algorithm is proposed to reconstruct the corresponding full-band frequency data. Firstly, the Complex Beta Process Factor Analysis (CBPFA) model is utilized to statistically model a set of full-band frequency data, whose probability density function (pdf) can be learned from this CBPFA model. Secondly, when the target is tracked and its attitude changes not much, the cognitive radar can just transmit the partial pulses of the stepped-frequency signal, and the corresponding full-band frequency data can be analytically reconstructed from the incomplete frequency data via the Compressive Sensing (CS) method and Bayesian criterion based on the previous pdf learned with CBPFA model. The reconstruction experiments of the measured HRR data demonstrate the performance of the proposed method.
It usually takes a long observing time when a cognitive radar transmits the High-Range-Resolution (HRR) stepped-frequency signal. To save time, partial pulses of the stepped-frequency signal are transmitted to obtain the incomplete frequency data, and a Bayesian reconstruction algorithm is proposed to reconstruct the corresponding full-band frequency data. Firstly, the Complex Beta Process Factor Analysis (CBPFA) model is utilized to statistically model a set of full-band frequency data, whose probability density function (pdf) can be learned from this CBPFA model. Secondly, when the target is tracked and its attitude changes not much, the cognitive radar can just transmit the partial pulses of the stepped-frequency signal, and the corresponding full-band frequency data can be analytically reconstructed from the incomplete frequency data via the Compressive Sensing (CS) method and Bayesian criterion based on the previous pdf learned with CBPFA model. The reconstruction experiments of the measured HRR data demonstrate the performance of the proposed method.
2015, 37(2): 322-327.
doi: 10.11999/JEIT141043
Abstract:
Transmit beampattern design for Multiple Input Multiple Output (MIMO) radar is obtained by synthesizing the signal covariance matrix, which can be achieved by convex optimization approaches. Due to the high computational complexity, these approaches are not easy for practical implementation. In this paper, a cyclic iterative method for MIMO radar transmit beampattern design is proposed. Based on the weighted least square criterion, signal covariance matrix can be obtained by optimizing the quadratic cost function with respect to its Hermite square root. For the uniform linear array, especially when the sampling grid in normalized spatial frequency is uniform and the weights for grid points are the same, FFT can be used to further reduce the computational complexity of the proposed algorithm. Simulation results show that the resulting beampattern matches the desired pattern closely and the proposed algorithm is efficient for the real time application.
Transmit beampattern design for Multiple Input Multiple Output (MIMO) radar is obtained by synthesizing the signal covariance matrix, which can be achieved by convex optimization approaches. Due to the high computational complexity, these approaches are not easy for practical implementation. In this paper, a cyclic iterative method for MIMO radar transmit beampattern design is proposed. Based on the weighted least square criterion, signal covariance matrix can be obtained by optimizing the quadratic cost function with respect to its Hermite square root. For the uniform linear array, especially when the sampling grid in normalized spatial frequency is uniform and the weights for grid points are the same, FFT can be used to further reduce the computational complexity of the proposed algorithm. Simulation results show that the resulting beampattern matches the desired pattern closely and the proposed algorithm is efficient for the real time application.
2015, 37(2): 328-333.
doi: 10.11999/JEIT140551
Abstract:
The K-distribution is usually used to model the Polarimetric Synthetic Aperture Radar (PolSAR) imagery. The parameter estimation method for K-distribution is very important,which affects the fitting degree of the model. However, the classical method of matrix log-cumulants relies upon a nontrivial inversion of a nonlinear equation, which introduces a computationally expensive stage into the estimation procedure. Moreover, the bias is large when the sharp parameter is smaller than 1. Therefore, a new method for estimating the sharp parameter of K-distribution based on|z|rlg|z| is proposed. This method is more adaptable to parameter estimation under different sharp parameters, and the performance is better than matrix log-cumulantes whenis small. In addition, the proposed estimator has an analytical expression at r=1/d, which allows rapid caculation. Finally, the estimation accuracy of this new estimator is compared with previous ones through simulation data and real data. The results show that the new estimator is effective and robust, which is of practical value in solving the accurate parameter estimation of K-distribution.
The K-distribution is usually used to model the Polarimetric Synthetic Aperture Radar (PolSAR) imagery. The parameter estimation method for K-distribution is very important,which affects the fitting degree of the model. However, the classical method of matrix log-cumulants relies upon a nontrivial inversion of a nonlinear equation, which introduces a computationally expensive stage into the estimation procedure. Moreover, the bias is large when the sharp parameter is smaller than 1. Therefore, a new method for estimating the sharp parameter of K-distribution based on|z|rlg|z| is proposed. This method is more adaptable to parameter estimation under different sharp parameters, and the performance is better than matrix log-cumulantes whenis small. In addition, the proposed estimator has an analytical expression at r=1/d, which allows rapid caculation. Finally, the estimation accuracy of this new estimator is compared with previous ones through simulation data and real data. The results show that the new estimator is effective and robust, which is of practical value in solving the accurate parameter estimation of K-distribution.
2015, 37(2): 334-338.
doi: 10.11999/JEIT140508
Abstract:
The traditional post-Doppler adaptive processing approaches such as Factored Approach (FA) and Extended Factored Approach (EFA) can significantly reduce the computation-cost and training sample requirement in adaptive processing. However, their clutter suppression ability is considerably degraded with the increasing number of antenna elements. To solve this problem, a two-stage reduced-dimension adaptive processing method based on the decomposition of spatial data is proposed. This method decomposes the spatial data after Doppler filtering into a Kronecker product of two short vectors. Then a bi-quadratic cost function is obtained. The circular iteration is applied to solve the optimal weight. Experimental results show that the proposed method has the advantages of fast convergence and small training samples requirement. It has greater clutter suppression ability especially in small training samples support compared with FA and EFA.
The traditional post-Doppler adaptive processing approaches such as Factored Approach (FA) and Extended Factored Approach (EFA) can significantly reduce the computation-cost and training sample requirement in adaptive processing. However, their clutter suppression ability is considerably degraded with the increasing number of antenna elements. To solve this problem, a two-stage reduced-dimension adaptive processing method based on the decomposition of spatial data is proposed. This method decomposes the spatial data after Doppler filtering into a Kronecker product of two short vectors. Then a bi-quadratic cost function is obtained. The circular iteration is applied to solve the optimal weight. Experimental results show that the proposed method has the advantages of fast convergence and small training samples requirement. It has greater clutter suppression ability especially in small training samples support compared with FA and EFA.
2015, 37(2): 339-345.
doi: 10.11999/JEIT140338
Abstract:
This paper focuses on Two Dimensional (2D) geometric feature inversion method of midcourse targets, serving for the target recognition problem of ballistic missile defense system. Based on the figuration characteristic of midcourse targets, a stable characteristic quantity, which describes the 2D geometric configuration of target, is proposed. The characteristic quantity is independent on the target attitude variation and radar work condition. Then the expression form of 2D geometric feature in radar image is analyzed with respect to different intervals, the mapping relationships between ISAR images under various target attitudes and the 2D geometric feature of target are established, and an 2D geometric feature inversion method for midcourse targets based on ISAR image is proposed. The proposed method can stably estimate the 2D geometric feature of midcourse targets under all attitudes during the midcourse flight, which is verified by the simulation experiments with electromagnetic computed data and measured data in anechoic chamber.
This paper focuses on Two Dimensional (2D) geometric feature inversion method of midcourse targets, serving for the target recognition problem of ballistic missile defense system. Based on the figuration characteristic of midcourse targets, a stable characteristic quantity, which describes the 2D geometric configuration of target, is proposed. The characteristic quantity is independent on the target attitude variation and radar work condition. Then the expression form of 2D geometric feature in radar image is analyzed with respect to different intervals, the mapping relationships between ISAR images under various target attitudes and the 2D geometric feature of target are established, and an 2D geometric feature inversion method for midcourse targets based on ISAR image is proposed. The proposed method can stably estimate the 2D geometric feature of midcourse targets under all attitudes during the midcourse flight, which is verified by the simulation experiments with electromagnetic computed data and measured data in anechoic chamber.
2015, 37(2): 346-352.
doi: 10.11999/JEIT140317
Abstract:
In order to solve the problem of the ghost and the shadow of moving object, an improved Visual Background extractor (ViBe) algorithm is proposed based on gray feature and adaptive threshold. The new method firstly applies the ViBe algorithm to obtain the foreground object, and then uses the gray feature judgment, as well as the adaptive threshold comparison in the foreground object to get the moving object without the ghost and the shadow. Experiments show that the improved algorithm results in better recognition accuracy.
In order to solve the problem of the ghost and the shadow of moving object, an improved Visual Background extractor (ViBe) algorithm is proposed based on gray feature and adaptive threshold. The new method firstly applies the ViBe algorithm to obtain the foreground object, and then uses the gray feature judgment, as well as the adaptive threshold comparison in the foreground object to get the moving object without the ghost and the shadow. Experiments show that the improved algorithm results in better recognition accuracy.
2015, 37(2): 353-359.
doi: 10.11999/JEIT140370
Abstract:
The Leap Motion sensor can detect the position and speed information of hands and fingers with high precision in real-time, which provides an effective way for volume interaction with large screen at long-distance. A set of understandable gesture for volume interaction is designed by observing gestures of the users to control the remote real objects. By dividing the near and far field regions of the Leap Motion sensor, a reasonable mapping between physics space and information space is established. According to the estimation solution for hand orientation with Depth Camera, an orientation estimation algorithm combining hand normal vector with fingertip vector is proposed using Leap Motion sensor. In addition, a non touching volume interaction prototype is designed for large screen application, and the prototype evaluation is given through the user experiment. Experimental results show that the proposed algorithm can provide a more natural, intuitive and efficient user experience compared with the traditional 2D volume interaction.
The Leap Motion sensor can detect the position and speed information of hands and fingers with high precision in real-time, which provides an effective way for volume interaction with large screen at long-distance. A set of understandable gesture for volume interaction is designed by observing gestures of the users to control the remote real objects. By dividing the near and far field regions of the Leap Motion sensor, a reasonable mapping between physics space and information space is established. According to the estimation solution for hand orientation with Depth Camera, an orientation estimation algorithm combining hand normal vector with fingertip vector is proposed using Leap Motion sensor. In addition, a non touching volume interaction prototype is designed for large screen application, and the prototype evaluation is given through the user experiment. Experimental results show that the proposed algorithm can provide a more natural, intuitive and efficient user experience compared with the traditional 2D volume interaction.
2015, 37(2): 360-366.
doi: 10.11999/JEIT140363
Abstract:
With the increasing of the air traffic flow, conflict detection plays an increasingly important role in air traffic management system. A probabilistic conflict detection algorithm is proposed. Overall conflict probability in look-ahead time is calculated. The aircraft predicted trajectory is expressed as deterministic trajectory plus a Brownian motion perturbation. For the case of constant aircraft speed, conflict probability is expressed as the probability of an aircraft with Brownian motion perturbation entering a time-varying moving protection zone, the probability is approximated using coordinate transformation and Bachelier-Levy theorem. For the case of aircraft with non-constant speed, predicted trajectory can be approximated by a large enough number of constant speed segments. Conflict probability of each segment is calculated and the overall conflict probability bounds in look-ahead time are given. Compared with Monte Carlo simulations, the proposed algorithm is accurate for conflict detection and it is useful to detect and avoid conflicts in air traffic management system.
With the increasing of the air traffic flow, conflict detection plays an increasingly important role in air traffic management system. A probabilistic conflict detection algorithm is proposed. Overall conflict probability in look-ahead time is calculated. The aircraft predicted trajectory is expressed as deterministic trajectory plus a Brownian motion perturbation. For the case of constant aircraft speed, conflict probability is expressed as the probability of an aircraft with Brownian motion perturbation entering a time-varying moving protection zone, the probability is approximated using coordinate transformation and Bachelier-Levy theorem. For the case of aircraft with non-constant speed, predicted trajectory can be approximated by a large enough number of constant speed segments. Conflict probability of each segment is calculated and the overall conflict probability bounds in look-ahead time are given. Compared with Monte Carlo simulations, the proposed algorithm is accurate for conflict detection and it is useful to detect and avoid conflicts in air traffic management system.
2015, 37(2): 367-372.
doi: 10.11999/JEIT140602
Abstract:
The traditional ElectroOculoGram (EOG) correction methods usually use the correlation information of multi-channel ElectroEncephaloGram (EEG), and are difficult to apply to portable Brain-Computer Interface (BCI) in single channel. An automatic EOG separation method is proposed based on the long term difference amplitude envelope and the wavelet transformation in the paper. Firstly, the accurate EOG beginning and ending points are detected on the long term difference amplitude envelope of the original EEG through a dual thresholds method. Secondly, the sym5 wavelet is applied to decompose the original EEG signal, and the Birg_Massart strategy is introduced to adaptively determine the thresholds of wavelet coefficients. Finally, the EOG is accurately reconstructed and separated from the EEG in this channel. Compared with the popular regression analysis of averaging artifact and the Independent Component Analysis (ICA) based methods, the proposed method is proved to achieve a better correlation measure between the separated EOG and the original EOG, a higher signal-to-noise ratio of the corrected EEG, and a good real-time operating speed for most BCI application requirements.
The traditional ElectroOculoGram (EOG) correction methods usually use the correlation information of multi-channel ElectroEncephaloGram (EEG), and are difficult to apply to portable Brain-Computer Interface (BCI) in single channel. An automatic EOG separation method is proposed based on the long term difference amplitude envelope and the wavelet transformation in the paper. Firstly, the accurate EOG beginning and ending points are detected on the long term difference amplitude envelope of the original EEG through a dual thresholds method. Secondly, the sym5 wavelet is applied to decompose the original EEG signal, and the Birg_Massart strategy is introduced to adaptively determine the thresholds of wavelet coefficients. Finally, the EOG is accurately reconstructed and separated from the EEG in this channel. Compared with the popular regression analysis of averaging artifact and the Independent Component Analysis (ICA) based methods, the proposed method is proved to achieve a better correlation measure between the separated EOG and the original EOG, a higher signal-to-noise ratio of the corrected EEG, and a good real-time operating speed for most BCI application requirements.
2015, 37(2): 373-379.
doi: 10.11999/JEIT140274
Abstract:
In stereophonic Acoustic Echo Cancellation (AEC) systems, the strong correlation between the two stereophonic channels leads to nonuniqueness of adaptive solutions and further large filter misalignment. To solve this problem and preserve speech quality, the psychoacoustic spectral dominance effect is utilized to propose a novel hybrid decorrelation method for stereo AEC. According to spectral dominance, weak sinusoids are injected at the three lowest harmonics so as to reduce low-frequency coherence. Besides, the nonlinear transformation method is modified and applied to high-frequency decorrelation. Comparison test on several performances with traditional approaches is carried out. Results show that the proposed method can effectively improve filter misalignment together with convergence rate. Moreover, low speech distortion can be achieved simultaneously.
In stereophonic Acoustic Echo Cancellation (AEC) systems, the strong correlation between the two stereophonic channels leads to nonuniqueness of adaptive solutions and further large filter misalignment. To solve this problem and preserve speech quality, the psychoacoustic spectral dominance effect is utilized to propose a novel hybrid decorrelation method for stereo AEC. According to spectral dominance, weak sinusoids are injected at the three lowest harmonics so as to reduce low-frequency coherence. Besides, the nonlinear transformation method is modified and applied to high-frequency decorrelation. Comparison test on several performances with traditional approaches is carried out. Results show that the proposed method can effectively improve filter misalignment together with convergence rate. Moreover, low speech distortion can be achieved simultaneously.
2015, 37(2): 380-385.
doi: 10.11999/JEIT140578
Abstract:
In the array signal processing, the inverse beamforming for interference suppression algorithm uses the azimuth information of interference to estimate and suppress the interference. In the complex marine environment the phase of the interference which is received by the array has the random disturbances, there is a big deviation between the actual interference and the interference which is estimated by the algorithm, which makes the effect of the interference suppression not good. In order to adapt the random disturbances of the phase of the interference, the inverse beamforming for interference suppression algorithm with good robust takes the random disturbances into full consideration and uses the interference reconstruction matrix to estimate the interference. In this case the estimated interference is closer to the actual interference signal and the result of interference suppression is better. The proposed method takes the random disturbances of the phase of the interference into full consideration, so it shows good robust in the complex ocean environment. Both the theoretical analysis and the computer simulation results show the effectiveness of the proposed method.
In the array signal processing, the inverse beamforming for interference suppression algorithm uses the azimuth information of interference to estimate and suppress the interference. In the complex marine environment the phase of the interference which is received by the array has the random disturbances, there is a big deviation between the actual interference and the interference which is estimated by the algorithm, which makes the effect of the interference suppression not good. In order to adapt the random disturbances of the phase of the interference, the inverse beamforming for interference suppression algorithm with good robust takes the random disturbances into full consideration and uses the interference reconstruction matrix to estimate the interference. In this case the estimated interference is closer to the actual interference signal and the result of interference suppression is better. The proposed method takes the random disturbances of the phase of the interference into full consideration, so it shows good robust in the complex ocean environment. Both the theoretical analysis and the computer simulation results show the effectiveness of the proposed method.
2015, 37(2): 386-393.
doi: 10.11999/JEIT140161
Abstract:
Combining one-class classifiers using the classical ensemble methods is not satisfactory. To address this problem, this paper first proves that though one-class classification performance can be improved by a classifier ensemble, it can also degrade if the set of base classifiers are not selected carefully. On this basis, this study further analyzes that the lacking of diversity heavily accounts for performance degradation. Therefore, a hybrid method for generating diverse base classifiers is proposed. Secondly, in the combining phase, to find the most useful diversity, the one-class ensemble loss is split and analyzed theoretically to propose a diversity based pruning method. Finally, by combining these two steps, a novel ensemble one-class classifier named Pruned Hybrid Diverse Ensemble One-class Classifier (PHD-EOC) is proposed. The experimental results on the UCI datasets and a malicious software detection dataset show that the PHD-EOC strikes a better balance between the diverse base classifiers and classification performance. It also outperforms other classical ensemble methods for a faster decision speed.
Combining one-class classifiers using the classical ensemble methods is not satisfactory. To address this problem, this paper first proves that though one-class classification performance can be improved by a classifier ensemble, it can also degrade if the set of base classifiers are not selected carefully. On this basis, this study further analyzes that the lacking of diversity heavily accounts for performance degradation. Therefore, a hybrid method for generating diverse base classifiers is proposed. Secondly, in the combining phase, to find the most useful diversity, the one-class ensemble loss is split and analyzed theoretically to propose a diversity based pruning method. Finally, by combining these two steps, a novel ensemble one-class classifier named Pruned Hybrid Diverse Ensemble One-class Classifier (PHD-EOC) is proposed. The experimental results on the UCI datasets and a malicious software detection dataset show that the PHD-EOC strikes a better balance between the diverse base classifiers and classification performance. It also outperforms other classical ensemble methods for a faster decision speed.
2015, 37(2): 394-398.
doi: 10.11999/JEIT140538
Abstract:
To cope with the issue of determining cyclic shift coefficients of the quasi-cyclic sub-matrix in the Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes, a method is presented based on the Arithmetic Progression (AP) to compute the cyclic shift coefficients. By this method, the girth of its Tanner graph is at least eight, and the cyclic shift coefficients can be expressed in simple analytic expressions to reduce required memory usage. The simulation results show that the proposed algorithm has high flexibility with respect to the design of code length and rate. Furthermore, over an Additive White Gauss Noise (AWGN) channel and under the Belief Propagation (BP) decoding algorithm, the simulation result also represents that the SNR of the proposed QC-LDPC codes is better than the Progressive Edge-Growth (PEG) codes close to 0.3 dB at the code length of 1008 and BER performance of 10-5.
To cope with the issue of determining cyclic shift coefficients of the quasi-cyclic sub-matrix in the Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes, a method is presented based on the Arithmetic Progression (AP) to compute the cyclic shift coefficients. By this method, the girth of its Tanner graph is at least eight, and the cyclic shift coefficients can be expressed in simple analytic expressions to reduce required memory usage. The simulation results show that the proposed algorithm has high flexibility with respect to the design of code length and rate. Furthermore, over an Additive White Gauss Noise (AWGN) channel and under the Belief Propagation (BP) decoding algorithm, the simulation result also represents that the SNR of the proposed QC-LDPC codes is better than the Progressive Edge-Growth (PEG) codes close to 0.3 dB at the code length of 1008 and BER performance of 10-5.
2015, 37(2): 399-404.
doi: 10.11999/JEIT140339
Abstract:
A joint resource allocation algorithm is proposed to solve the problem of the proportional fairness and the system efficiency in multi-radio systems based on OFDMA (Orthogonal Frequency Division Multiple Access). The algorithm optimizes the system throughput under the fairness constraint, and considers that the allocated bandwidth should be integer times of the subchannel bandwidth. The bandwidth allocated to each terminal is adjusted according to this consideration. The performance of the proposed algorithm is evaluated by simulations in terms of the system throughput and the fairness.
A joint resource allocation algorithm is proposed to solve the problem of the proportional fairness and the system efficiency in multi-radio systems based on OFDMA (Orthogonal Frequency Division Multiple Access). The algorithm optimizes the system throughput under the fairness constraint, and considers that the allocated bandwidth should be integer times of the subchannel bandwidth. The bandwidth allocated to each terminal is adjusted according to this consideration. The performance of the proposed algorithm is evaluated by simulations in terms of the system throughput and the fairness.
2015, 37(2): 405-410.
doi: 10.11999/JEIT140472
Abstract:
The downlink transmission performance of the massive MIMO Time Division Duplex (TDD) system is bottlenecked by the channel reciprocity errors called antenna reciprocity errors. Antenna reciprocity errors are caused by the mismatch and mutual coupling between antennas. In order to compensate antenna reciprocity errors of the base station, a reciprocity calibration algorithm is proposed in this paper, which can reduce the impact of channel estimate errors by using total least square estimation and increasing channel measurement samples. Rayleigh quotient iteration is also used to reduce the complexity of the reciprocity calibration algorithm in this paper. Simulation results reveal that the algorithm proposed in this paper can achieve 1.8 dB performance gain with respect to the traditional one proposed in references when the antenna reciprocity errors of user equipments are ignored. When the antenna reciprocity errors of user equipments are considered,the performance of the proposed algorithm increases with the decreasing variance of the channel estimation errors.
The downlink transmission performance of the massive MIMO Time Division Duplex (TDD) system is bottlenecked by the channel reciprocity errors called antenna reciprocity errors. Antenna reciprocity errors are caused by the mismatch and mutual coupling between antennas. In order to compensate antenna reciprocity errors of the base station, a reciprocity calibration algorithm is proposed in this paper, which can reduce the impact of channel estimate errors by using total least square estimation and increasing channel measurement samples. Rayleigh quotient iteration is also used to reduce the complexity of the reciprocity calibration algorithm in this paper. Simulation results reveal that the algorithm proposed in this paper can achieve 1.8 dB performance gain with respect to the traditional one proposed in references when the antenna reciprocity errors of user equipments are ignored. When the antenna reciprocity errors of user equipments are considered,the performance of the proposed algorithm increases with the decreasing variance of the channel estimation errors.
2015, 37(2): 411-416.
doi: 10.11999/JEIT140542
Abstract:
Inter-cell interference is a major factor that limits the performance of multi-cell systems. In this paper, a cooperative scheduling and power control algorithm for Single-Carrier Frequency-Division Multiple Access (SC-FDMA) multi-cell systems is proposed to deal with the inter-cell interference in Long Term Evolution (LTE) uplink. It performs scheduling and power control for each cell separately, which schedules users first and then configures the transmit power for each user. The proposed algorithm performs scheduling by first estimating the inter-cell interference and then assigning resources to users. When optimizing the users transmit power, the performance variation of both the objective cell and other interfering cells is considered. Furthermore, a power control algorithm with low-complexity is proposed, which only considers the performance change of several cells interfered most by the objective cell and estimates the performance change of all other cells by introducing a compensation factor, when optimizing the transmit power of each user. Simulation results demonstrate the effectiveness of the proposed algorithm in cell average and cell edge throughput.
Inter-cell interference is a major factor that limits the performance of multi-cell systems. In this paper, a cooperative scheduling and power control algorithm for Single-Carrier Frequency-Division Multiple Access (SC-FDMA) multi-cell systems is proposed to deal with the inter-cell interference in Long Term Evolution (LTE) uplink. It performs scheduling and power control for each cell separately, which schedules users first and then configures the transmit power for each user. The proposed algorithm performs scheduling by first estimating the inter-cell interference and then assigning resources to users. When optimizing the users transmit power, the performance variation of both the objective cell and other interfering cells is considered. Furthermore, a power control algorithm with low-complexity is proposed, which only considers the performance change of several cells interfered most by the objective cell and estimates the performance change of all other cells by introducing a compensation factor, when optimizing the transmit power of each user. Simulation results demonstrate the effectiveness of the proposed algorithm in cell average and cell edge throughput.
2015, 37(2): 417-422.
doi: 10.11999/JEIT140373
Abstract:
FOX family block ciphers are based on Lai-Massey scheme. Firstly, the evaluation is performed on the ability of the reduced round FOX64 to resist zero-correlation linear cryptanalysis, and some 4-round zero- correlation linear distinguishers are presented. Then, by using the relation between the integral distinguishers and zero-correlation distinguishers, the 4-round integral distinguishers of FOX64 are found. Finally, the 4-round integral distinguishers are used to attack 5, 6, 7 and 8 rounds FOX64 with the time complexity of 252.7, 2116.7, 2180.7 and 2244.7 encryptions respectively, and the data complexity is 250 chosen plaintexts. This is the first paper pointing out that 8-round FOX64/256 is vulnerable against the statistical attack.
FOX family block ciphers are based on Lai-Massey scheme. Firstly, the evaluation is performed on the ability of the reduced round FOX64 to resist zero-correlation linear cryptanalysis, and some 4-round zero- correlation linear distinguishers are presented. Then, by using the relation between the integral distinguishers and zero-correlation distinguishers, the 4-round integral distinguishers of FOX64 are found. Finally, the 4-round integral distinguishers are used to attack 5, 6, 7 and 8 rounds FOX64 with the time complexity of 252.7, 2116.7, 2180.7 and 2244.7 encryptions respectively, and the data complexity is 250 chosen plaintexts. This is the first paper pointing out that 8-round FOX64/256 is vulnerable against the statistical attack.
2015, 37(2): 423-428.
doi: 10.11999/JEIT140421
Abstract:
User revocation is crucial to the practical application of Identity Based Encryption (IBE). The first Revocable Identity Based Encryption (RIBE) scheme from lattice is given by Chen et al. in ACISP 2012, but its security can only be proved in the selective-ID model. Using the IBE scheme suggested by Agrawal et al. in EUROCPYPT 2010, this paper constructs a lattice-based adaptive-ID secure RIBE scheme, so as to solve a problem left open by Chen et al.. This paper also points out that using the blocking technique given by Singh et al. in SPACE 2012, the public key size can be reduced effectively.
User revocation is crucial to the practical application of Identity Based Encryption (IBE). The first Revocable Identity Based Encryption (RIBE) scheme from lattice is given by Chen et al. in ACISP 2012, but its security can only be proved in the selective-ID model. Using the IBE scheme suggested by Agrawal et al. in EUROCPYPT 2010, this paper constructs a lattice-based adaptive-ID secure RIBE scheme, so as to solve a problem left open by Chen et al.. This paper also points out that using the blocking technique given by Singh et al. in SPACE 2012, the public key size can be reduced effectively.
2015, 37(2): 429-434.
doi: 10.11999/JEIT140901
Abstract:
An OQPSK modulation scheme used spread spectrum is proposed which is based on the Chinese medical band. The analysis is done under variety of interference, the simulation results indicate that this scheme has good performance of the broadband interference suppression, but is sensitive to the narrowband interference because of high false alarm rates of frame detection. A new frame detection algorithm based on twice delayed-autocorrelation is proposed, and it is verified that the algorithm exhibits better performance for narrowband and wideband interferences. The recording results of this paper can provide technical reference for standards development of wireless body area network standards. Currently, this scheme has been adopted in IEEE802.15.4n.
An OQPSK modulation scheme used spread spectrum is proposed which is based on the Chinese medical band. The analysis is done under variety of interference, the simulation results indicate that this scheme has good performance of the broadband interference suppression, but is sensitive to the narrowband interference because of high false alarm rates of frame detection. A new frame detection algorithm based on twice delayed-autocorrelation is proposed, and it is verified that the algorithm exhibits better performance for narrowband and wideband interferences. The recording results of this paper can provide technical reference for standards development of wireless body area network standards. Currently, this scheme has been adopted in IEEE802.15.4n.
2015, 37(2): 435-442.
doi: 10.11999/JEIT140246
Abstract:
How to efficiently cache and take advantage of largely distributed copies poses challenges to the retrieval process of Named Data Networking (NDN). On the basis of similarity in local request, a collaborative caching and routing scheme is proposed. In the scheme, redundancy elimination in vertical requesting path and collaborative cache in horizontal local scope are effectively combined on the caching decision-making. In the vertical direction, the similar community which has the highest active value along the content delivery path is calculated based on the path caching strategy. In the horizontal direction, consistent Hash-caching is implemented to fulfill the oriented cache for the requested data in the vicinity. When a retrieve is requested, the proposed scheme dynamically performs the local lookup according to the content popularity by introduction of the local cache factor into the routing process. The simulation results show that the scheme can decrease the request latency, reduce the cache redundancy, and achieve higher cache hit ratio by comparison with existing methods.
How to efficiently cache and take advantage of largely distributed copies poses challenges to the retrieval process of Named Data Networking (NDN). On the basis of similarity in local request, a collaborative caching and routing scheme is proposed. In the scheme, redundancy elimination in vertical requesting path and collaborative cache in horizontal local scope are effectively combined on the caching decision-making. In the vertical direction, the similar community which has the highest active value along the content delivery path is calculated based on the path caching strategy. In the horizontal direction, consistent Hash-caching is implemented to fulfill the oriented cache for the requested data in the vicinity. When a retrieve is requested, the proposed scheme dynamically performs the local lookup according to the content popularity by introduction of the local cache factor into the routing process. The simulation results show that the scheme can decrease the request latency, reduce the cache redundancy, and achieve higher cache hit ratio by comparison with existing methods.
2015, 37(2): 443-448.
doi: 10.11999/JEIT140333
Abstract:
Considering the limited cache resources of nodes in intermittently connected wireless networks, a cache management mechanism is proposed based on node state estimate. The direct and indirect connection status, service rate and connectivity degree between the given nodes can be evaluated in a distributed manner, according to the network state monitored during the movement. Further, the difference of service ability of each node can be determined dynamically. Furthermore, the probability of message successfully delivered by the current node and the utility for the given message can be estimated. Consequently, cache management operations are executed reasonably. Simulation results show that the proposed mechanism does not only constrain the overhead ratio effectively but also enhance the message delivery ratio, compared with other mechanisms.
Considering the limited cache resources of nodes in intermittently connected wireless networks, a cache management mechanism is proposed based on node state estimate. The direct and indirect connection status, service rate and connectivity degree between the given nodes can be evaluated in a distributed manner, according to the network state monitored during the movement. Further, the difference of service ability of each node can be determined dynamically. Furthermore, the probability of message successfully delivered by the current node and the utility for the given message can be estimated. Consequently, cache management operations are executed reasonably. Simulation results show that the proposed mechanism does not only constrain the overhead ratio effectively but also enhance the message delivery ratio, compared with other mechanisms.
2015, 37(2): 455-460.
doi: 10.11999/JEIT140514
Abstract:
Based on the stability theory of fractional-order system and Lyapunov stability theory, and using the sliding mode adaptive control and projective method, a synchronization control strategy is proposed for a class of fractional-order chaotic systems with uncertain parameters, uncertain nonlinear functions and external disturbances. A stable fractional-order integral sliding surface is selected and the adaptive laws are designed to estimate the uncertainties, consequently, the synchronization controller is obtained. Then, the projective method is introduced to modify above basic adaptive laws to prevent the adaptive parameters from diverging to infinite, thus, the boundedness of the control inputs is guaranteed. Finally, the numerical simulation result is presented to show the effectiveness and applicability of the proposed control strategy.
Based on the stability theory of fractional-order system and Lyapunov stability theory, and using the sliding mode adaptive control and projective method, a synchronization control strategy is proposed for a class of fractional-order chaotic systems with uncertain parameters, uncertain nonlinear functions and external disturbances. A stable fractional-order integral sliding surface is selected and the adaptive laws are designed to estimate the uncertainties, consequently, the synchronization controller is obtained. Then, the projective method is introduced to modify above basic adaptive laws to prevent the adaptive parameters from diverging to infinite, thus, the boundedness of the control inputs is guaranteed. Finally, the numerical simulation result is presented to show the effectiveness and applicability of the proposed control strategy.
2015, 37(2): 461-467.
doi: 10.11999/JEIT140063
Abstract:
According to the generation mechanism of the underwater corrosion-relative-electromagnetic field of submarine, a current-line which is regarded as end-to-end electric dipole is proposed to simulate the field distribution. Firstly, the underwater static electric field of a submarine model is calculated respectively by the boundary-element method and the current-line method, and the contrastive analysis of the calculation results shows it is feasible that the current-line mode is selected to estimate the underwater corrosion-relative- electromagnetic field of submarine. Then, based on the magnetic field expressions of the horizontal static electric dipole in layered-conductive media, the static corrosion-relative-magnetic field distribution of the submarine in all the space is simulated and analyzed. The simulation results show that, the near-field of the magnetic field in air is suitable to be as a new target of the aerial submarine hunting because of its measurable magnitude and obvious distribution characteristic, as well as the far-field is suitable to be as signal source for remote detection or position fixing of the degaussing submarine because it degenerates with the inverse square of the distance. The typical research results lay the foundation for the further application research.
According to the generation mechanism of the underwater corrosion-relative-electromagnetic field of submarine, a current-line which is regarded as end-to-end electric dipole is proposed to simulate the field distribution. Firstly, the underwater static electric field of a submarine model is calculated respectively by the boundary-element method and the current-line method, and the contrastive analysis of the calculation results shows it is feasible that the current-line mode is selected to estimate the underwater corrosion-relative- electromagnetic field of submarine. Then, based on the magnetic field expressions of the horizontal static electric dipole in layered-conductive media, the static corrosion-relative-magnetic field distribution of the submarine in all the space is simulated and analyzed. The simulation results show that, the near-field of the magnetic field in air is suitable to be as a new target of the aerial submarine hunting because of its measurable magnitude and obvious distribution characteristic, as well as the far-field is suitable to be as signal source for remote detection or position fixing of the degaussing submarine because it degenerates with the inverse square of the distance. The typical research results lay the foundation for the further application research.
2015, 37(2): 468-476.
doi: 10.11999/JEIT140295
Abstract:
To evaluate effects of process variations on circuit delay accurately, this study proposes a Statistical Static Timing Analysis (SSTA) which incorporates process variations with spatial correlations. The algorithm applies a second order delay model that taking into account the non-Gaussian parameters - by inducting the notion of conditional variables, the 2D non-linear delay model is translated into 1D linear one; and by computing the tightness probability, mean, variance, second-order moment and sensitivity coefficients of the circuit arrival time, the sum and max operations of non-linear and non-Gaussian delay expressions are implemented. For the ISCAS89 benchmark circuits, as compared to Monte Carlo (MC) simulation, the average errors of 0.81%, -0.72%, 2.23% and -0.05%, in the mean, variance, 5% and 95% quantile points of the circuit delay are obtained respectively for the proposed method. The runtime of the proposed method is about 0.21% of the value of Monte Carlo simulation. The experimental results prove that the high accuracy of the SSTA is reliable.
To evaluate effects of process variations on circuit delay accurately, this study proposes a Statistical Static Timing Analysis (SSTA) which incorporates process variations with spatial correlations. The algorithm applies a second order delay model that taking into account the non-Gaussian parameters - by inducting the notion of conditional variables, the 2D non-linear delay model is translated into 1D linear one; and by computing the tightness probability, mean, variance, second-order moment and sensitivity coefficients of the circuit arrival time, the sum and max operations of non-linear and non-Gaussian delay expressions are implemented. For the ISCAS89 benchmark circuits, as compared to Monte Carlo (MC) simulation, the average errors of 0.81%, -0.72%, 2.23% and -0.05%, in the mean, variance, 5% and 95% quantile points of the circuit delay are obtained respectively for the proposed method. The runtime of the proposed method is about 0.21% of the value of Monte Carlo simulation. The experimental results prove that the high accuracy of the SSTA is reliable.
2015, 37(2): 477-483.
doi: 10.11999/JEIT140165
Abstract:
As Through-Silicon-Vias (TSVs) in three-Dimensional Network-on-Chip (3D NoC) accompany some overhead such as the cost and the area, in order to optimize the number of TSVs of 3D NoC in test mode and reduce the test time, a new method using evolution algorithm based on cloud model is proposed to research on the test scheduling of 3D NoC and the impact of TSVs number and their allocation in each layer on 3D NoC test. This method combines the cloud evolution algorithm with niche technology and hybridization technique in genetic algorithm. It uses effectively the concepts of heredity, natural selection and community diversity to improve the quality of the algorithm on optimizing speed and precision. Experimental results demonstrate that the proposed method can not only effectively prevent from running into local optimization solution, but also improve the ability and speed of searching the best solution, and that TSVs number of 3D NoC can be optimized to improve the TSVs utilization.
As Through-Silicon-Vias (TSVs) in three-Dimensional Network-on-Chip (3D NoC) accompany some overhead such as the cost and the area, in order to optimize the number of TSVs of 3D NoC in test mode and reduce the test time, a new method using evolution algorithm based on cloud model is proposed to research on the test scheduling of 3D NoC and the impact of TSVs number and their allocation in each layer on 3D NoC test. This method combines the cloud evolution algorithm with niche technology and hybridization technique in genetic algorithm. It uses effectively the concepts of heredity, natural selection and community diversity to improve the quality of the algorithm on optimizing speed and precision. Experimental results demonstrate that the proposed method can not only effectively prevent from running into local optimization solution, but also improve the ability and speed of searching the best solution, and that TSVs number of 3D NoC can be optimized to improve the TSVs utilization.
2015, 37(2): 484-488.
doi: 10.11999/JEIT140362
Abstract:
During GPS outages, the foot-mounted inertial-based sensors are common replacement in pedestrian navigation. The Zero velocity UPdaTe-aided Extended Kalman Filter (ZUPT-aided EKF) is often used to resolve the trajectory of a walking pedestrian with acceleration and angular rate measurements from foot-mounted sensors. However, the trajectory suffers from long-term drifts, which needs to be calibrated. This paper proposes a particle filter based approach for trajectory calibration, which exploits apriori knowledge of building structures to update particle weight. The buildings are supposed to have four domain directions, which is defined by the layout of corridors. The navigation frame is divided by eight directions, including four domain directions and four complementary directions, and the weight is assigned according to the eight directions using a Gaussian function. Finally, several real-scenario experiments are carried out, which can demonstrate that the proposed approach have better accuracy and consistency than the results without calibration or traditional methods, as the proposed approach can reach a location error of 2.7 m in a complex-trajectory walk of 861 m and the accuracy is better than 0.5%; the fact that the location error remains below 2 m in different floors also demonstrates the good consistency of the approach. As a result, the proposed approach can perform stable and continuous positioning.
During GPS outages, the foot-mounted inertial-based sensors are common replacement in pedestrian navigation. The Zero velocity UPdaTe-aided Extended Kalman Filter (ZUPT-aided EKF) is often used to resolve the trajectory of a walking pedestrian with acceleration and angular rate measurements from foot-mounted sensors. However, the trajectory suffers from long-term drifts, which needs to be calibrated. This paper proposes a particle filter based approach for trajectory calibration, which exploits apriori knowledge of building structures to update particle weight. The buildings are supposed to have four domain directions, which is defined by the layout of corridors. The navigation frame is divided by eight directions, including four domain directions and four complementary directions, and the weight is assigned according to the eight directions using a Gaussian function. Finally, several real-scenario experiments are carried out, which can demonstrate that the proposed approach have better accuracy and consistency than the results without calibration or traditional methods, as the proposed approach can reach a location error of 2.7 m in a complex-trajectory walk of 861 m and the accuracy is better than 0.5%; the fact that the location error remains below 2 m in different floors also demonstrates the good consistency of the approach. As a result, the proposed approach can perform stable and continuous positioning.
2015, 37(2): 494-498.
doi: 10.11999/JEIT140434
Abstract:
The simulation of 3D Chinese ink painting style is an important research topic of the Non-Photorealistic Rendering (NPR). The traditional rendering methods are mostly confined to black and white ink. This paper puts forward a contour optimization of multi-channel 3D ink rendering model. Firstly, this method completes the inner coloring of multi-color ink by using the illumination model with the Alpha channel. Then it achieves contour stylization by means of the grid model expansion and texture map. Lastly, it hides the excess contours on the Alpha channel through the table priority algorithm of 3D depth sorting method for achieving the output of 3D Chinese ink rendering images. The experimental results demonstrate that the rendering effects under contour stylization provide more vivid ink effects. And the output of multi-channel images facilitates the following images procession as well.
The simulation of 3D Chinese ink painting style is an important research topic of the Non-Photorealistic Rendering (NPR). The traditional rendering methods are mostly confined to black and white ink. This paper puts forward a contour optimization of multi-channel 3D ink rendering model. Firstly, this method completes the inner coloring of multi-color ink by using the illumination model with the Alpha channel. Then it achieves contour stylization by means of the grid model expansion and texture map. Lastly, it hides the excess contours on the Alpha channel through the table priority algorithm of 3D depth sorting method for achieving the output of 3D Chinese ink rendering images. The experimental results demonstrate that the rendering effects under contour stylization provide more vivid ink effects. And the output of multi-channel images facilitates the following images procession as well.
2015, 37(2): 504-508.
doi: 10.11999/JEIT140232
Abstract:
Bzip2, a lossless compression algorithm, is widely used in recent years because of its high compression ratio. Burrows-Wheeler Transform (BWT) is the key factor in Bzip2. This method can gather the same symbols together. The traditional methods which are based on suffix sorting used in implement of BWT in hardware can solve the problem of memory consumption effectively. Detail analysis of BWT algorithm based on suffix sorting is given and a new methodSuffix segment method is presented in this paper. Experimental results show that the proposed method can much decrease BWT time consumption without increasing memory consumption much.
Bzip2, a lossless compression algorithm, is widely used in recent years because of its high compression ratio. Burrows-Wheeler Transform (BWT) is the key factor in Bzip2. This method can gather the same symbols together. The traditional methods which are based on suffix sorting used in implement of BWT in hardware can solve the problem of memory consumption effectively. Detail analysis of BWT algorithm based on suffix sorting is given and a new methodSuffix segment method is presented in this paper. Experimental results show that the proposed method can much decrease BWT time consumption without increasing memory consumption much.
2015, 37(2): 449-454.
doi: 10.11999/JEIT140512
Abstract:
To cluster the directed and large-scale social networks, a Structural Clustering Algorithm for Directed Networks (DirSCAN) and a corresponding Parallel algorithm (PDirSCAN) are proposed. Considering oriented behavioral relation between two vertices, DirSCAN is constructed based on action structural similarity and function analysis. To meet the need of large-scale social network analysis, a lossless PDirSCAN based on MapReduce distributed parallel architecture is designed to improve the processing performance. A large number of experimental results on real-world network datasets show that DirSCAN improves performance of SCAN up to 2.34% on F1, PDirSCAN runs 1.67 times faster than DirSCAN.
To cluster the directed and large-scale social networks, a Structural Clustering Algorithm for Directed Networks (DirSCAN) and a corresponding Parallel algorithm (PDirSCAN) are proposed. Considering oriented behavioral relation between two vertices, DirSCAN is constructed based on action structural similarity and function analysis. To meet the need of large-scale social network analysis, a lossless PDirSCAN based on MapReduce distributed parallel architecture is designed to improve the processing performance. A large number of experimental results on real-world network datasets show that DirSCAN improves performance of SCAN up to 2.34% on F1, PDirSCAN runs 1.67 times faster than DirSCAN.
2015, 37(2): 499-503.
doi: 10.11999/JEIT140340
Abstract:
This paper proposes an improved Hidden Markov Model (HMM) based multimedia traffic classification method. This method preserves the classical HMM model structure, and improves the performance of multimedia traffic classification by changing the emitting probability value with the position information of packet size. Theoretical analysis indicates that the new model can reduce the computational complexity of the classical HMM model. Simulation results show that the proposed method can improve the classification performance compared with the existing HMM based classification method.
This paper proposes an improved Hidden Markov Model (HMM) based multimedia traffic classification method. This method preserves the classical HMM model structure, and improves the performance of multimedia traffic classification by changing the emitting probability value with the position information of packet size. Theoretical analysis indicates that the new model can reduce the computational complexity of the classical HMM model. Simulation results show that the proposed method can improve the classification performance compared with the existing HMM based classification method.
2015, 37(2): 489-493.
doi: 10.11999/JEIT140166
Abstract:
A quadratic estimation algorithm is proposed to reduce the complexity of accurate Linear Frequency Modulation (LFM) parameter estimation. First, the frequency rate and initial frequency are estimated coarsely by short time coherent integral and incoherent accumulation. Then, the parallel Partial Matched Filters combined with FFT (PMF-FFT) and quadratic interpolation are utilized to estimate the residuals of the frequency rate and initial frequency. Last, the final estimated values are obtained by synthesizing the results of both estimations. Simulation shows that the proposed algorithm has a low SNR threshold, and the accuracy is close to Cramer-Rao Lower Bound (CRLB). The complexity and hardware consumption of the proposed algorithm are much less than the frequency rate test algorithm and joint estimation algorithm based on interpolation.
A quadratic estimation algorithm is proposed to reduce the complexity of accurate Linear Frequency Modulation (LFM) parameter estimation. First, the frequency rate and initial frequency are estimated coarsely by short time coherent integral and incoherent accumulation. Then, the parallel Partial Matched Filters combined with FFT (PMF-FFT) and quadratic interpolation are utilized to estimate the residuals of the frequency rate and initial frequency. Last, the final estimated values are obtained by synthesizing the results of both estimations. Simulation shows that the proposed algorithm has a low SNR threshold, and the accuracy is close to Cramer-Rao Lower Bound (CRLB). The complexity and hardware consumption of the proposed algorithm are much less than the frequency rate test algorithm and joint estimation algorithm based on interpolation.
