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2012 Vol. 34, No. 9
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2012, 34(9): 2033-2038.
doi: 10.3724/SP.J.1146.2012.00021
Abstract:
To increase signal number distinguished by traditional MUSIC algorithm, this paper proposes a MUSIC algorithm based on three-dimensional smoothing by a coprime pair of two-dimensional sparse electromagnetic vector arrays. The coprime relationship between two arrays is used in the algorithm to generate a coprime co-array with more degrees of freedom. And the rank of its autocorrelation matrix is restored by three-dimensional (two-dimensional spatial domain and polarization domain) smoothing algorithm in order to apply to the traditional MUSIC algorithm. A major advantage of this method is that the freedom of the original array is also systematically increased by even using second-order statistics. Computer simulation results show that the proposed algorithm can estimate the number of signals more than the number of physical array elements and have high resolution.
To increase signal number distinguished by traditional MUSIC algorithm, this paper proposes a MUSIC algorithm based on three-dimensional smoothing by a coprime pair of two-dimensional sparse electromagnetic vector arrays. The coprime relationship between two arrays is used in the algorithm to generate a coprime co-array with more degrees of freedom. And the rank of its autocorrelation matrix is restored by three-dimensional (two-dimensional spatial domain and polarization domain) smoothing algorithm in order to apply to the traditional MUSIC algorithm. A major advantage of this method is that the freedom of the original array is also systematically increased by even using second-order statistics. Computer simulation results show that the proposed algorithm can estimate the number of signals more than the number of physical array elements and have high resolution.
2012, 34(9): 2039-2044.
doi: 10.3724/SP.J.1146.2012.00150
Abstract:
To solve the problems of traditional methods for mixing matrix estimation in blind source separation such as poor robustness, the defect that separation performance is vulnerable to the initial value and low estimation accuracy, Artificial Bee Colony (ABC) algorithm is applied to blind source separation. Combining with the characteristics of mixing matrix estimation for sparse signals separation, a two-stage bee colony algorithm based on different searching strategy and encoding mode is proposed to estimate mixing matrix, which can accelerate the convergence rate and enhance estimation precision through bees new searching behavior and collaboration between the bee colonies. The simulation results show that the proposed method can perform very well even in the case of large-scale, weak sparse and low SNR. The proposed method not only has the characteristics of strong robustness and high estimation accuracy compared with existing methods, but also need not a large amount of calculation.
To solve the problems of traditional methods for mixing matrix estimation in blind source separation such as poor robustness, the defect that separation performance is vulnerable to the initial value and low estimation accuracy, Artificial Bee Colony (ABC) algorithm is applied to blind source separation. Combining with the characteristics of mixing matrix estimation for sparse signals separation, a two-stage bee colony algorithm based on different searching strategy and encoding mode is proposed to estimate mixing matrix, which can accelerate the convergence rate and enhance estimation precision through bees new searching behavior and collaboration between the bee colonies. The simulation results show that the proposed method can perform very well even in the case of large-scale, weak sparse and low SNR. The proposed method not only has the characteristics of strong robustness and high estimation accuracy compared with existing methods, but also need not a large amount of calculation.
2012, 34(9): 2045-2050.
doi: 10.3724/SP.J.1146.2012.00118
Abstract:
A nonlinear adaptive beamforming approach based on Least-Square Support Vector Regression (LS-SVR) is proposed to enhance the beamformers robustness against array model mismatch, constrained samples numerous interferences, etc. The approach has two highlights, one is a recursive regression procedure to compute the regression parameters on real-time, the other is a sparse mode based on novelty criterion, which can significantly reduce the size of the input samples. Applying the sparse model to LS-SVR beamforming leads to reduced computation complexity and better generalization capacity. The theory analysis and experimental results show that the proposed beamforming approach could improve array performance significantly over several classical linear beamforming methods.
A nonlinear adaptive beamforming approach based on Least-Square Support Vector Regression (LS-SVR) is proposed to enhance the beamformers robustness against array model mismatch, constrained samples numerous interferences, etc. The approach has two highlights, one is a recursive regression procedure to compute the regression parameters on real-time, the other is a sparse mode based on novelty criterion, which can significantly reduce the size of the input samples. Applying the sparse model to LS-SVR beamforming leads to reduced computation complexity and better generalization capacity. The theory analysis and experimental results show that the proposed beamforming approach could improve array performance significantly over several classical linear beamforming methods.
2012, 34(9): 2051-2057.
doi: 10.3724/SP.J.1146.2012.00146
Abstract:
To overcome effectively the influence of large steering vector mismatch on the performance of adaptive beamformer, a Robust Adaptive Beamformer using Decomposition and Iterative Second-Order Cone Programming via Worst-Case performance optimization (RAB-DISOCP-WC) is proposed in this paper. Due to the decomposition and iterative method for the non-convex magnitude response constraints, the problem can be optimally solved using iterative Second-Order Cone Programming (SOCP), then the beamwidth and ripple of the robust response region can be flexibly controlled by the proposed method, and the output Signal-to- Interference-and-Noise Ratio (SINR) can be obviously improved. Moreover, in constrast to most of this class of robust beamformers, the proposed approach can get the optimal weight vector directly, and it does not need any spectral factorization. Thus, the proposed approach does not have any array geometry constraint, and it is applicable to arbitrary array geometries. Simulation results verify the correctness and validity of the proposed approach.
To overcome effectively the influence of large steering vector mismatch on the performance of adaptive beamformer, a Robust Adaptive Beamformer using Decomposition and Iterative Second-Order Cone Programming via Worst-Case performance optimization (RAB-DISOCP-WC) is proposed in this paper. Due to the decomposition and iterative method for the non-convex magnitude response constraints, the problem can be optimally solved using iterative Second-Order Cone Programming (SOCP), then the beamwidth and ripple of the robust response region can be flexibly controlled by the proposed method, and the output Signal-to- Interference-and-Noise Ratio (SINR) can be obviously improved. Moreover, in constrast to most of this class of robust beamformers, the proposed approach can get the optimal weight vector directly, and it does not need any spectral factorization. Thus, the proposed approach does not have any array geometry constraint, and it is applicable to arbitrary array geometries. Simulation results verify the correctness and validity of the proposed approach.
2012, 34(9): 2058-2063.
doi: 10.3724/SP.J.1146.2012.00203
Abstract:
In order to make the color edge detector considering the discrimination of human eyes, avoiding the perceptually insigni?cant edges being over-detected, a novel color gradient based color-edge detection algorithm based on the adaptive perceptual color difference is proposed. A weighting factor including luminance masking effect and contrast sensitivity function is proposed, which combine the influence of local changes in luminance and spatial frequency to human visual system. The SNR and the quality factor Pratt of edge detection evaluation and the time complexity show that the proposed method can detect the color image edge accurately and against the effect of noise.
In order to make the color edge detector considering the discrimination of human eyes, avoiding the perceptually insigni?cant edges being over-detected, a novel color gradient based color-edge detection algorithm based on the adaptive perceptual color difference is proposed. A weighting factor including luminance masking effect and contrast sensitivity function is proposed, which combine the influence of local changes in luminance and spatial frequency to human visual system. The SNR and the quality factor Pratt of edge detection evaluation and the time complexity show that the proposed method can detect the color image edge accurately and against the effect of noise.
2012, 34(9): 2064-2070.
doi: 10.3724/SP.J.1146.2012.00047
Abstract:
The Bag of Words (BoW) model is applied to object classification in this paper. An optimized method based on the combination of Region Of Interest (ROI) extraction and pyramid matching scheme is proposed to optimize and improve the traditional model in order to overcome the disadvantages. First, the ROI is extracted from training images and then the codebook is generated using the features which are extracted from the ROI instead of the entire images using dense Scale-Invariant Feature Transform (SIFT) descriptor. Therefore, the codebook can describe the features of the images more accurately and also can resist the impact of the various position information as well as background. Then the images will be represented as the histogram of codebook using pyramid matching scheme as the input of Support Vector Machine (SVM) classifier. The experiments are carried out based both Caltech 101 and Caltech 256 database. The results show that the proposed method performs better than the traditional method and the state of the art. What is more, the classification accuracy is good even though under lack of training images.
The Bag of Words (BoW) model is applied to object classification in this paper. An optimized method based on the combination of Region Of Interest (ROI) extraction and pyramid matching scheme is proposed to optimize and improve the traditional model in order to overcome the disadvantages. First, the ROI is extracted from training images and then the codebook is generated using the features which are extracted from the ROI instead of the entire images using dense Scale-Invariant Feature Transform (SIFT) descriptor. Therefore, the codebook can describe the features of the images more accurately and also can resist the impact of the various position information as well as background. Then the images will be represented as the histogram of codebook using pyramid matching scheme as the input of Support Vector Machine (SVM) classifier. The experiments are carried out based both Caltech 101 and Caltech 256 database. The results show that the proposed method performs better than the traditional method and the state of the art. What is more, the classification accuracy is good even though under lack of training images.
2012, 34(9): 2071-2077.
doi: 10.3724/SP.J.1146.2012.00088
Abstract:
A novel method of?locating and quantifying the color errors introduced by subpixel addressing technology in color matrix displays is proposed. According to the spatial color blending of human visions, the paper indicates that the measurement of color errors should be performed within multi-scale region of color blending. Taking rectangular arrangement of subpixels as an example, the shape and size of the multi-scale blending region is designed base on the structure basis of lattice theory, and color errors locating and quantifying is achieved. Analysis and experiments show that the adaptive method of eliminating color errors based on the multi-scale blending region can keep more original image details while weaken color errors efficiently.
A novel method of?locating and quantifying the color errors introduced by subpixel addressing technology in color matrix displays is proposed. According to the spatial color blending of human visions, the paper indicates that the measurement of color errors should be performed within multi-scale region of color blending. Taking rectangular arrangement of subpixels as an example, the shape and size of the multi-scale blending region is designed base on the structure basis of lattice theory, and color errors locating and quantifying is achieved. Analysis and experiments show that the adaptive method of eliminating color errors based on the multi-scale blending region can keep more original image details while weaken color errors efficiently.
2012, 34(9): 2078-2084.
doi: 10.3724/SP.J.1146.2012.00005
Abstract:
In the application of image segmentation based on fast level set algorithm, there exist difficulties in level set initialization and setting thresholds, so a new algorithm which combining PYRamid model, Random Walk and Level Set (PYR-RW-LS) is proposed. First, the multi-scale analysis technique is introduced into Random Walk (RW) algorithm, and its partition result is taken as the initialized curve of the fast level set algorithm, so the fast level set algorithms initialization problem is solved; Then the evolution of the level set can be seen as the constant pattern classification of the points on the curve. Both Bayesian classification rule and minimal distance classification rule were introduced by this new algorithm to work alternatively, in order to acquire the driving force for curve evolution. And the invalidation conditions for both of the classification rules are set as the iteration stop conditions in this new algorithm, thus solving the difficulties in setting thresholds. Simulating experimental results show that PYR-RW-LS not only runs faster than the fast level set algorithm, which only adopts pattern classification ideas, but also has better capabilities than RW algorithm in terms of anti-noise capabilities; And the advantages of being insensitive to blurry boundaries remains with the RW algorithm. PYR-RW-LS algorithm, therefore, is good in particular, for images with large size and high resolution.
In the application of image segmentation based on fast level set algorithm, there exist difficulties in level set initialization and setting thresholds, so a new algorithm which combining PYRamid model, Random Walk and Level Set (PYR-RW-LS) is proposed. First, the multi-scale analysis technique is introduced into Random Walk (RW) algorithm, and its partition result is taken as the initialized curve of the fast level set algorithm, so the fast level set algorithms initialization problem is solved; Then the evolution of the level set can be seen as the constant pattern classification of the points on the curve. Both Bayesian classification rule and minimal distance classification rule were introduced by this new algorithm to work alternatively, in order to acquire the driving force for curve evolution. And the invalidation conditions for both of the classification rules are set as the iteration stop conditions in this new algorithm, thus solving the difficulties in setting thresholds. Simulating experimental results show that PYR-RW-LS not only runs faster than the fast level set algorithm, which only adopts pattern classification ideas, but also has better capabilities than RW algorithm in terms of anti-noise capabilities; And the advantages of being insensitive to blurry boundaries remains with the RW algorithm. PYR-RW-LS algorithm, therefore, is good in particular, for images with large size and high resolution.
2012, 34(9): 2085-2090.
doi: 10.3724/SP.J.1146.2012.00125
Abstract:
This paper put forth a technique called Error-Detecting Network of Pronunciation (EDNP) that is applied to Computer Assisted Language Learning (CALL) system. By comparison with state-of-the-art CALL systems, the application of this kind of network is to insert mispronunciation detection routes into task-specific Finite State Grammar (FSG) network and avoid constructing complex mispronounced models. The detailed procedures of how to construct mispronunciation detection network and how to perform an error callback strategy are introduced in this paper. The algorithm is simply to be implemented and is independent to any speech toolkit. The experiments show that the application of this network achieves a False Acceptance Rate (FAR) of 7.38%, as well as a False Rejection Rate (FRR) of 12.25% for the deletion errors and achieves a FAR of 4.94%, as well as a FRR of 26.17% for the insertion errors. Furthermore, compared to traditional forced alignment, there is 4.29% improvement to correlation rate between the objective and the subjective pronunciation quality evaluation by using EDNP.
This paper put forth a technique called Error-Detecting Network of Pronunciation (EDNP) that is applied to Computer Assisted Language Learning (CALL) system. By comparison with state-of-the-art CALL systems, the application of this kind of network is to insert mispronunciation detection routes into task-specific Finite State Grammar (FSG) network and avoid constructing complex mispronounced models. The detailed procedures of how to construct mispronunciation detection network and how to perform an error callback strategy are introduced in this paper. The algorithm is simply to be implemented and is independent to any speech toolkit. The experiments show that the application of this network achieves a False Acceptance Rate (FAR) of 7.38%, as well as a False Rejection Rate (FRR) of 12.25% for the deletion errors and achieves a FAR of 4.94%, as well as a FRR of 26.17% for the insertion errors. Furthermore, compared to traditional forced alignment, there is 4.29% improvement to correlation rate between the objective and the subjective pronunciation quality evaluation by using EDNP.
2012, 34(9): 2091-2096.
doi: 10.3724/SP.J.1146.2012.00398
Abstract:
A novel algorithm named Iterative combination of a Local nearest Neighbor search step and a Conversion step Alignment (ILNCA), a modified version of the Iterative combination of a nearest Neighor search step and a Conversion step Alignment (INCA), is proposed for training voice conversion system under the situation of nonparallel corpus. Unlike INCA, ILNCA uses firstly Gaussian Mixture Model (GMM) to represent the spectral feature spaces of both source speaker and target speaker respectively, and then matches each individual Gaussian components of the GMM from source speaker to target speaker and vice versa according to Kullback-Leibler (KL) distance. Finally, ILNCA performs the frame alignment of phonetically equivalent acoustic vectors from source and target speaker in their mapped sub-spaces, not in the whole space like INCA. Both object and subject evaluations are conducted. The experimental results demonstrate that the approach can achieve better performance than INCA because of the accurate vector alignment.
A novel algorithm named Iterative combination of a Local nearest Neighbor search step and a Conversion step Alignment (ILNCA), a modified version of the Iterative combination of a nearest Neighor search step and a Conversion step Alignment (INCA), is proposed for training voice conversion system under the situation of nonparallel corpus. Unlike INCA, ILNCA uses firstly Gaussian Mixture Model (GMM) to represent the spectral feature spaces of both source speaker and target speaker respectively, and then matches each individual Gaussian components of the GMM from source speaker to target speaker and vice versa according to Kullback-Leibler (KL) distance. Finally, ILNCA performs the frame alignment of phonetically equivalent acoustic vectors from source and target speaker in their mapped sub-spaces, not in the whole space like INCA. Both object and subject evaluations are conducted. The experimental results demonstrate that the approach can achieve better performance than INCA because of the accurate vector alignment.
2012, 34(9): 2097-2102.
doi: 10.3724/SP.J.1146.2012.00172
Abstract:
This paper focuses on automatic scoring about ask-and-answer item in large scale of spoken English test. Three kinds of features are extracted to score based on the text from Automatic Speech Recognition (ASR). They are similarity features, parser features and features about speech. All of nine features describe the relation with human raters from different aspects. Among features of similarity measure, Manhattan distance is converted into similarity to improve the performance of scoring. Furthermore, keywords coverage rate based on edit distance is proposed to distinguish words variation in order to give students a more objective score. All of those features are put into multiple linear regression model to score. The experiment results show that performance of automatic scoring system based on speakers achieves 98.4% of human raters.
This paper focuses on automatic scoring about ask-and-answer item in large scale of spoken English test. Three kinds of features are extracted to score based on the text from Automatic Speech Recognition (ASR). They are similarity features, parser features and features about speech. All of nine features describe the relation with human raters from different aspects. Among features of similarity measure, Manhattan distance is converted into similarity to improve the performance of scoring. Furthermore, keywords coverage rate based on edit distance is proposed to distinguish words variation in order to give students a more objective score. All of those features are put into multiple linear regression model to score. The experiment results show that performance of automatic scoring system based on speakers achieves 98.4% of human raters.
2012, 34(9): 2103-2109.
doi: 10.3724/SP.J.1146.2012.00097
Abstract:
Incorporated with digital beamforming processing, along-track multi-channel spaceborne SAR systems are promising in High-Resolution and Wide-Swath (HRWS) imaging by overcoming the minimum antenna area constraint. In this paper, a common phase compensating equation for multi-static space-borne SAR systems is given. Then, it is proved that the optimum capon method can keep the phase quality, and the orbit parameters of each sample are obtained for the following SAR interferometry processing and target locating. Finally, the proposed method is validated using the simulated data based on the ellipse earth model.
Incorporated with digital beamforming processing, along-track multi-channel spaceborne SAR systems are promising in High-Resolution and Wide-Swath (HRWS) imaging by overcoming the minimum antenna area constraint. In this paper, a common phase compensating equation for multi-static space-borne SAR systems is given. Then, it is proved that the optimum capon method can keep the phase quality, and the orbit parameters of each sample are obtained for the following SAR interferometry processing and target locating. Finally, the proposed method is validated using the simulated data based on the ellipse earth model.
2012, 34(9): 2110-2115.
doi: 10.3724/SP.J.1146.2012.00200
Abstract:
After analyzing the causes of SAR image noise and speckle model, a SAR image de-noising method is presented in Shearlet domain from the theory of image sparse representation. The proposed algorithm is to de-noise SAR image from the entire image information: firstly, Shearlet transform is applied to the noise SAR image, then, the de-noised Shearlet coefficients are got based on iterative de-noising algorithm from noise optimization model which constructed by the model of sparse representation of the SAR image, finally, the clean SAR image is obtained from the de-nosing Shearlet coefficients. The experimental results show that the proposed algorithm can suppress speckle and improve the PSNR of de-noised image significantly, as well as improve visual effect of the image and retain the image texture information better.
After analyzing the causes of SAR image noise and speckle model, a SAR image de-noising method is presented in Shearlet domain from the theory of image sparse representation. The proposed algorithm is to de-noise SAR image from the entire image information: firstly, Shearlet transform is applied to the noise SAR image, then, the de-noised Shearlet coefficients are got based on iterative de-noising algorithm from noise optimization model which constructed by the model of sparse representation of the SAR image, finally, the clean SAR image is obtained from the de-nosing Shearlet coefficients. The experimental results show that the proposed algorithm can suppress speckle and improve the PSNR of de-noised image significantly, as well as improve visual effect of the image and retain the image texture information better.
2012, 34(9): 2116-2121.
doi: 10.3724/SP.J.1146.2012.00147
Abstract:
This paper studies on the classification issue of turbojet, propeller and helicopter targets by using the conventional radar system. Based on the micro-Doppler effect, the echo signal model for the rotating parts of aircrafts is analyzed theoretically via the multi-scattering center model firstly. Then according to the differences between the frequency modulation properties of the three kinds of airplanes in the Doppler domain, a new feature extraction method is proposed based on the Empirical Mode Decomposition (EMD) algorithm. Finally, the experimental results with the simulated training data, the measured test data and the Support Vector Machine (SVM) show the proposed method can achieve good classification performance under the test condition of relatively high Signal-to-Noise Ratio (SNR).
This paper studies on the classification issue of turbojet, propeller and helicopter targets by using the conventional radar system. Based on the micro-Doppler effect, the echo signal model for the rotating parts of aircrafts is analyzed theoretically via the multi-scattering center model firstly. Then according to the differences between the frequency modulation properties of the three kinds of airplanes in the Doppler domain, a new feature extraction method is proposed based on the Empirical Mode Decomposition (EMD) algorithm. Finally, the experimental results with the simulated training data, the measured test data and the Support Vector Machine (SVM) show the proposed method can achieve good classification performance under the test condition of relatively high Signal-to-Noise Ratio (SNR).
2012, 34(9): 2122-2127.
doi: 10.3724/SP.J.1146.2012.00071
Abstract:
Micro-motion feature is one of the effective features used for radar target recognition in the middle section of the ballistic curve. To solve the problem of estimating spinning and structural parameters based on the micro-Doppler of the spinning warhead with fins in bistatic radar, the micro-Doppler models of the scattering centers at the edge of fins and the conjunction of the fins and the body of warhead are derived when the warhead is spinning firstly. Then the bistatic scattering coefficients of the warhead model are calculated by using FEKO. The micro-Doppler models are verified from the time frequency analysis on the bistatic scattering coefficients, and the characteristics of the micro-Doppler are summarized. Thirdly, the feasibility of extracting spinning and structural parameters in bistatic radar is analysed. Finally, because Hough transform can not estimate the parameters because of the flashes, a new idea to extract the parameters using the flashes is proposed.
Micro-motion feature is one of the effective features used for radar target recognition in the middle section of the ballistic curve. To solve the problem of estimating spinning and structural parameters based on the micro-Doppler of the spinning warhead with fins in bistatic radar, the micro-Doppler models of the scattering centers at the edge of fins and the conjunction of the fins and the body of warhead are derived when the warhead is spinning firstly. Then the bistatic scattering coefficients of the warhead model are calculated by using FEKO. The micro-Doppler models are verified from the time frequency analysis on the bistatic scattering coefficients, and the characteristics of the micro-Doppler are summarized. Thirdly, the feasibility of extracting spinning and structural parameters in bistatic radar is analysed. Finally, because Hough transform can not estimate the parameters because of the flashes, a new idea to extract the parameters using the flashes is proposed.
2012, 34(9): 2128-2134.
doi: 10.3724/SP.J.1146.2012.00053
Abstract:
Considering the polarization parameters of target are not usually unknown in Polarization Space Time Adaptive Processing (PSTAP), a new method which filters after estimating polarization state is advanced. The new method is deemed to reduce the computation, because which is not using a filter bank to cover the whole polarization domain. Firstly, the Minimum Variance Unbiased (MVU) estimator and Orthogonal Projection (OP) estimator are developed. Then, the Cramer-Rao Bounds (CRB) for MVU estimation of the target polarization parameters are briefly derived. The performance of MVU estimator is superior to OP estimator. Finally, the new PSTAP method performed significantly better than the traditional optimum space-time processing technology, especially in the case of the target slowly moving. Simulations demonstrate the correctness of models.
Considering the polarization parameters of target are not usually unknown in Polarization Space Time Adaptive Processing (PSTAP), a new method which filters after estimating polarization state is advanced. The new method is deemed to reduce the computation, because which is not using a filter bank to cover the whole polarization domain. Firstly, the Minimum Variance Unbiased (MVU) estimator and Orthogonal Projection (OP) estimator are developed. Then, the Cramer-Rao Bounds (CRB) for MVU estimation of the target polarization parameters are briefly derived. The performance of MVU estimator is superior to OP estimator. Finally, the new PSTAP method performed significantly better than the traditional optimum space-time processing technology, especially in the case of the target slowly moving. Simulations demonstrate the correctness of models.
2012, 34(9): 2135-2142.
doi: 10.3724/SP.J.1146.2011.01393
Abstract:
Alternate transmission and reception is an effective way to obtain a longer along-track baseline and additional independent phase centers to improve the performance of Ground Moving Target Indication (GMTI) in single-platform multi-channel SAR systems. A theoretic analysis of the signal model of moving targets in multi-channel SAR systems with alternate transmission and reception is made. And the necessary condition for the existence of the along-track baseline is indicated. Based on the signal model and the theoretical derivation, the design consideration of the modes of alternate transmission and reception is given. The comparison of GMTI performance with different antenna partitions and alternating strategies shows that an appropriate antenna partition and alternating strategy is important in improving the GMTI performance. The correctness of the conclusion is experimentally verified by the simulated and real SAR data.
Alternate transmission and reception is an effective way to obtain a longer along-track baseline and additional independent phase centers to improve the performance of Ground Moving Target Indication (GMTI) in single-platform multi-channel SAR systems. A theoretic analysis of the signal model of moving targets in multi-channel SAR systems with alternate transmission and reception is made. And the necessary condition for the existence of the along-track baseline is indicated. Based on the signal model and the theoretical derivation, the design consideration of the modes of alternate transmission and reception is given. The comparison of GMTI performance with different antenna partitions and alternating strategies shows that an appropriate antenna partition and alternating strategy is important in improving the GMTI performance. The correctness of the conclusion is experimentally verified by the simulated and real SAR data.
2012, 34(9): 2143-2148.
doi: 10.3724/SP.J.1146.2012.00220
Abstract:
In this paper, a method based on Nonlinear Least Squares (NLS) is presented for detecting the maneuvering aerial targets with the strong clutter background. Firstly, the signal model of the target is constructed. Secondly, the data after clutter suppression is obtained. Then, the parameters of the targets can be estimated while using NLS through minimizing the sum of the squares of the distances between the former two. The method can provide an accurate estimate of the parameters even when the data sample is limited. The effectiveness of the method is verified via simulated data.
In this paper, a method based on Nonlinear Least Squares (NLS) is presented for detecting the maneuvering aerial targets with the strong clutter background. Firstly, the signal model of the target is constructed. Secondly, the data after clutter suppression is obtained. Then, the parameters of the targets can be estimated while using NLS through minimizing the sum of the squares of the distances between the former two. The method can provide an accurate estimate of the parameters even when the data sample is limited. The effectiveness of the method is verified via simulated data.
2012, 34(9): 2149-2155.
doi: 10.3724/SP.J.1146.2012.00362
Abstract:
The similarity measures between SAR images are the basis for target recognition, image registration and so on. In this paper, a new similarity measure for uncertain SAR images based on intensity increment code is proposed after analyzing the characteristics of existing methods. Firstly, the code image is obtained by averaging the difference of brightness in adjacent pixels in SAR images. Then, the similarity measure for uncertain SAR images is got by evaluating the concordance of code images. The proposed method is proved to be robust to speckle noise, partially occlusion and fuzzification through theoretical analysis in this paper and the SAR image matching at confidence level using the proposed method is discussed. The theoretical analysis and experimental results demonstrate that the proposed similarity measure is robust to the speckle noise, partially occlusion and fuzzification in SAR images and is valid for uncertain SAR image matching.
The similarity measures between SAR images are the basis for target recognition, image registration and so on. In this paper, a new similarity measure for uncertain SAR images based on intensity increment code is proposed after analyzing the characteristics of existing methods. Firstly, the code image is obtained by averaging the difference of brightness in adjacent pixels in SAR images. Then, the similarity measure for uncertain SAR images is got by evaluating the concordance of code images. The proposed method is proved to be robust to speckle noise, partially occlusion and fuzzification through theoretical analysis in this paper and the SAR image matching at confidence level using the proposed method is discussed. The theoretical analysis and experimental results demonstrate that the proposed similarity measure is robust to the speckle noise, partially occlusion and fuzzification in SAR images and is valid for uncertain SAR image matching.
2012, 34(9): 2156-2160.
doi: 10.3724/SP.J.1146.2012.00096
Abstract:
In this paper, the best linear approximation of addition modulo 2n is studied. Firstly, the formula for maximum correlations of addition modulo 2n is proposed by using the linear approximation of the coordinate functions of addition modulo 2n. Moreover, a method to construct the best linear approximation set of addition modulo 2n is given in a recursive way. The paper characterizes the inner principle of best linear approximation of addition modulo 2n theoretically, which will help to use the linear approximation relation to realize an effective analysis of cryptographic algorithms.
In this paper, the best linear approximation of addition modulo 2n is studied. Firstly, the formula for maximum correlations of addition modulo 2n is proposed by using the linear approximation of the coordinate functions of addition modulo 2n. Moreover, a method to construct the best linear approximation set of addition modulo 2n is given in a recursive way. The paper characterizes the inner principle of best linear approximation of addition modulo 2n theoretically, which will help to use the linear approximation relation to realize an effective analysis of cryptographic algorithms.
2012, 34(9): 2161-2166.
doi: 10.3724/SP.J.1146.2012.00201
Abstract:
LBlock is a lightweight block cipher designed by Wu Wen-ling et al. in 2011. In this paper, a specific related-key differential is uesd to attack 19-round LBlock. The attack finds all the 80 bit keys in O(270.0) 19-round encryptions.The data complexity is 264 chosen plaintexts. Further more, a related-key impossible differential attack to 21-round Lblock is proposed. With 263 chosen plaintexts, the computing complexity of the attack is about O(271.5) 21-round encryptions for obtaining key.
LBlock is a lightweight block cipher designed by Wu Wen-ling et al. in 2011. In this paper, a specific related-key differential is uesd to attack 19-round LBlock. The attack finds all the 80 bit keys in O(270.0) 19-round encryptions.The data complexity is 264 chosen plaintexts. Further more, a related-key impossible differential attack to 21-round Lblock is proposed. With 263 chosen plaintexts, the computing complexity of the attack is about O(271.5) 21-round encryptions for obtaining key.
2012, 34(9): 2167-2173.
doi: 10.3724/SP.J.1146.2012.00285
Abstract:
Since BGP (Border Gateway Protocol) possesses many security vulnerabilities, BGP Autonomous System PATH information (AS_PATH attribute) is vulnerable to various attacks. In proposed BGP path verification mechanisms at present, the high computational overhead and complex process severely block security solutions from being implemented and deployed in real world. A lightweight method is designed for BGP path verification named First-Two-AS based Path Verification (FTAPV). Based on analysis of AS_PATH attribute, FTAPV can protect path information effectively through carrying signatures of first two ASes in the AS_PATH of UPDATEs. Security analysis and performance evaluation demonstrate this mechanism can reduce the route resource expense and the number of used certificates with strong ability of security and good scalability compared with existing method.
Since BGP (Border Gateway Protocol) possesses many security vulnerabilities, BGP Autonomous System PATH information (AS_PATH attribute) is vulnerable to various attacks. In proposed BGP path verification mechanisms at present, the high computational overhead and complex process severely block security solutions from being implemented and deployed in real world. A lightweight method is designed for BGP path verification named First-Two-AS based Path Verification (FTAPV). Based on analysis of AS_PATH attribute, FTAPV can protect path information effectively through carrying signatures of first two ASes in the AS_PATH of UPDATEs. Security analysis and performance evaluation demonstrate this mechanism can reduce the route resource expense and the number of used certificates with strong ability of security and good scalability compared with existing method.
2012, 34(9): 2174-2179.
doi: 10.3724/SP.J.1146.2012.00236
Abstract:
The traditional Reference Broadcast Synchronization (RBS) algorithm has a problem that network overhead is very large as the network nodes increase in Wireless sensor networks. An Energy-efficient RBS (ERBS) scheme is presented to work out the network overhead issue. Firstly, every receiving node, which is required to receive a couple of reference messages, computes mean phase offset to its nonadjacent receiving nodes, and estimates phase offset by maximum posteriori estimation; Secondly, the algorithm uses least-squares linear regression to fit clock skew periodically. The analysis on simulation result indicates that ERBS algorithm improve synchronization precision and reduce energy usage over RBS.
The traditional Reference Broadcast Synchronization (RBS) algorithm has a problem that network overhead is very large as the network nodes increase in Wireless sensor networks. An Energy-efficient RBS (ERBS) scheme is presented to work out the network overhead issue. Firstly, every receiving node, which is required to receive a couple of reference messages, computes mean phase offset to its nonadjacent receiving nodes, and estimates phase offset by maximum posteriori estimation; Secondly, the algorithm uses least-squares linear regression to fit clock skew periodically. The analysis on simulation result indicates that ERBS algorithm improve synchronization precision and reduce energy usage over RBS.
2012, 34(9): 2180-2186.
doi: 10.3724/SP.J.1146.2011.01421
Abstract:
Considering the issue of nodes failure for energy heterogeneous wireless sensor networks, a new topology with Adjustable Degree Distribution (ADD) is constructed, and the formulas of degree distribution is obtained. And then through analyzing the effect of degree distribution characteristics on topology tolerance, the optimal topology is derived, which can assure the finish of network monitoring tasks for long under the integrated failure of nodes resulted from energy exhaust and environment damage. The simulation results show that the topology is more robustness, which provides longer lifetime.
Considering the issue of nodes failure for energy heterogeneous wireless sensor networks, a new topology with Adjustable Degree Distribution (ADD) is constructed, and the formulas of degree distribution is obtained. And then through analyzing the effect of degree distribution characteristics on topology tolerance, the optimal topology is derived, which can assure the finish of network monitoring tasks for long under the integrated failure of nodes resulted from energy exhaust and environment damage. The simulation results show that the topology is more robustness, which provides longer lifetime.
2012, 34(9): 2187-2193.
doi: 10.3724/SP.J.1146.2012.00059
Abstract:
Due to the limited communication capability and energy constraint of sensor nodes, a target tracking scheme is proposed for sensor networks based on Dynamic Cluster Routing Optimization and Distributed Particle Filter (DCRO-DPF). In order to achieve a balanced distribution of network energy consumption, DCRO-DPF utilizes a dynamic clustering approach to divide the nodes which deployed randomly in the monitored region into a number of clusters, then optimizes not only the communication routes between member nodes and cluster head in each cluster, but also the communication routes between cluster heads and the base station. On this basis, the activated cluster member nodes execute distributed particle filter to track the maneuvering target. The simulations corroborate that this scheme can effectively reduce the total energy consumption of the sensor networks, achieve the goal of tracking and guarantee the tracking accuracy simultaneously.
Due to the limited communication capability and energy constraint of sensor nodes, a target tracking scheme is proposed for sensor networks based on Dynamic Cluster Routing Optimization and Distributed Particle Filter (DCRO-DPF). In order to achieve a balanced distribution of network energy consumption, DCRO-DPF utilizes a dynamic clustering approach to divide the nodes which deployed randomly in the monitored region into a number of clusters, then optimizes not only the communication routes between member nodes and cluster head in each cluster, but also the communication routes between cluster heads and the base station. On this basis, the activated cluster member nodes execute distributed particle filter to track the maneuvering target. The simulations corroborate that this scheme can effectively reduce the total energy consumption of the sensor networks, achieve the goal of tracking and guarantee the tracking accuracy simultaneously.
A Dynamic Routing Mechanism Based on Collection Tree Protocol in Industrial Wireless Sensor Networks
2012, 34(9): 2194-2199.
doi: 10.3724/SP.J.1146.2012.00075
Abstract:
Wireless Highway Addressable Remote Transducer (HART) is the most widely applied standard to industrial wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the industrial wireless network applications. In this paper, a collection tree protocol based dynamic routing mechanism is proposed for industrial wireless sensor networks in the base of wireless HART protocol. This mechanism generates and maintains the network topology through occupying several time slots in the Time Division Multiple Address (TDMA) super frame. The dynamic routing mechanism is evaluated through several simulation experiments in three aspects: time for generating the topology, link quality and stability of network. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based industrial wireless sensor networks.
Wireless Highway Addressable Remote Transducer (HART) is the most widely applied standard to industrial wireless sensor networks nowadays. However, it does not provide any dynamic routing mechanism, which is important for the reliability and robustness of the industrial wireless network applications. In this paper, a collection tree protocol based dynamic routing mechanism is proposed for industrial wireless sensor networks in the base of wireless HART protocol. This mechanism generates and maintains the network topology through occupying several time slots in the Time Division Multiple Address (TDMA) super frame. The dynamic routing mechanism is evaluated through several simulation experiments in three aspects: time for generating the topology, link quality and stability of network. The simulation and evaluation results show that this mechanism can act as a dynamic routing mechanism for the TDMA-based industrial wireless sensor networks.
2012, 34(9): 2200-2207.
doi: 10.3724/SP.J.1146.2012.00019
Abstract:
In view of shortcomings of some methods for similarity measurement, like value dependent of series elements and insufficient mining of information in series, a new method for time series compartmentation, approximation representation and similar measurement is proposed in this paper. Based on sufficient mining of information and orderliness in series, the time series are divided into many sections and the curve fitting model of each section is established. Then, the time series are represented approximately with a sequence of the curvatures of each time in the sections, while the curvature distance is proposed. Finally, the similarity searching algorithms in time series based on curvature distance is proposed. It mines the information of the series sufficiently, retains and recognizes the major shape of the series effectively, experimental results prove the effectiveness, stability and accuracy of the method proposed in this paper.
In view of shortcomings of some methods for similarity measurement, like value dependent of series elements and insufficient mining of information in series, a new method for time series compartmentation, approximation representation and similar measurement is proposed in this paper. Based on sufficient mining of information and orderliness in series, the time series are divided into many sections and the curve fitting model of each section is established. Then, the time series are represented approximately with a sequence of the curvatures of each time in the sections, while the curvature distance is proposed. Finally, the similarity searching algorithms in time series based on curvature distance is proposed. It mines the information of the series sufficiently, retains and recognizes the major shape of the series effectively, experimental results prove the effectiveness, stability and accuracy of the method proposed in this paper.
2012, 34(9): 2208-2212.
doi: 10.3724/SP.J.1146.2012.00144
Abstract:
Narrowband interference from other systems degrades greatly the performance of Orthogonal Frequency Division Multiplexing (OFDM) systems in heterogeneous networks. This paper proposes a cyclostationarity-based narrowband interference suppression algorithm to estimate and suppress the interference, and derives the Signal to Interference plus Noise Ratio (SINR) gain. Simulation results show that the proposed algorithm outperforms the conventional linear prediction filtering method in estimating and suppressing interference, therefore improves the system performance.
Narrowband interference from other systems degrades greatly the performance of Orthogonal Frequency Division Multiplexing (OFDM) systems in heterogeneous networks. This paper proposes a cyclostationarity-based narrowband interference suppression algorithm to estimate and suppress the interference, and derives the Signal to Interference plus Noise Ratio (SINR) gain. Simulation results show that the proposed algorithm outperforms the conventional linear prediction filtering method in estimating and suppressing interference, therefore improves the system performance.
2012, 34(9): 2213-2217.
doi: 10.3724/SP.J.1146.2012.00309
Abstract:
A target channel visiting scheme which visits target channels in a descending order of channel mean vacant time duration is proposed for proactive decision spectrum handoff in cognitive radio. It proofs that this scheme result in minimum probability of handoff failure when the channel vacant time duration follows uniform distribution, Rayleigh distribution or Weibull distribution. Simulations show that the probability of handoff failure of this scheme is far lower than that of the random target channel visiting scheme. Moreover, when tens of samples of channel vacant time duration can be obtained, even though there is estimation error, the probability of handoff failure of the proposed scheme is very close to the optimal minimum probability.
A target channel visiting scheme which visits target channels in a descending order of channel mean vacant time duration is proposed for proactive decision spectrum handoff in cognitive radio. It proofs that this scheme result in minimum probability of handoff failure when the channel vacant time duration follows uniform distribution, Rayleigh distribution or Weibull distribution. Simulations show that the probability of handoff failure of this scheme is far lower than that of the random target channel visiting scheme. Moreover, when tens of samples of channel vacant time duration can be obtained, even though there is estimation error, the probability of handoff failure of the proposed scheme is very close to the optimal minimum probability.
2012, 34(9): 2218-2223.
doi: 10.3724/SP.J.1146.2012.00275
Abstract:
In high-speed mobile environment, the orthogonality between different subcarriers in OFDM is destroyed and the performance for system decreases rapidly. In this paper, the mathematical model of Doppler spread caused by high-speed mobility is analyzed and a novel multiple antennas angle resolution based transceiver algorithm is proposed. In this algorithm, orthogonal angle domain subspace projection is utilized. The Doppler spread is simplified as Doppler frequency offset on each orthogonal angle domain subspace and Doppler parameter estimation is utilized to suppress the effect caused by high-speed mobility. Simulation results show that the proposed algorithm suppress the inter-carrier-interference of OFDM in high-speed mobile environment effectively and can achieve performance improvement.
In high-speed mobile environment, the orthogonality between different subcarriers in OFDM is destroyed and the performance for system decreases rapidly. In this paper, the mathematical model of Doppler spread caused by high-speed mobility is analyzed and a novel multiple antennas angle resolution based transceiver algorithm is proposed. In this algorithm, orthogonal angle domain subspace projection is utilized. The Doppler spread is simplified as Doppler frequency offset on each orthogonal angle domain subspace and Doppler parameter estimation is utilized to suppress the effect caused by high-speed mobility. Simulation results show that the proposed algorithm suppress the inter-carrier-interference of OFDM in high-speed mobile environment effectively and can achieve performance improvement.
2012, 34(9): 2224-2229.
doi: 10.3724/SP.J.1146.2012.00251
Abstract:
A method of performance optimization is proposed based on Markov process in Heterogeneous Wireless Networks (HWNs) consisting of diverse wireless networks. The method takes users mobility as an important factor affecting system performance, and users mobility is embodied by handoff rate. Then the system performance of HWNs based on Markov process is analyzed, and the expression of total throughput is obtained for the performance analysis of HWNs. Considering that the users in the overlapping region of two wireless networks need to select one of them to access, the proportion of service arrival rate accessing to one of the networks to the total service arrival rate in the overlapping region is regarded as an optimized factor for performance analysis. The throughput of the HWNs system is maximized by choosing appropriate factor. Finally, the optimization issue is worked out based on golden section method. The simulation results show that the optimization algorithm can effectively enhance the throughput of HWNs, and improve the resources utilization of wireless networks.
A method of performance optimization is proposed based on Markov process in Heterogeneous Wireless Networks (HWNs) consisting of diverse wireless networks. The method takes users mobility as an important factor affecting system performance, and users mobility is embodied by handoff rate. Then the system performance of HWNs based on Markov process is analyzed, and the expression of total throughput is obtained for the performance analysis of HWNs. Considering that the users in the overlapping region of two wireless networks need to select one of them to access, the proportion of service arrival rate accessing to one of the networks to the total service arrival rate in the overlapping region is regarded as an optimized factor for performance analysis. The throughput of the HWNs system is maximized by choosing appropriate factor. Finally, the optimization issue is worked out based on golden section method. The simulation results show that the optimization algorithm can effectively enhance the throughput of HWNs, and improve the resources utilization of wireless networks.
2012, 34(9): 2230-2235.
doi: 10.3724/SP.J.1146.2012.00121
Abstract:
Wireless Access Points (APs) deployed in the same hotspot with a high density will cause channel interference. Considering this issue, also combined with the QoS of terminals in the same Basic Service Set (BSS) and the load balance among different BSS, a three-dimensional discrete Markov chain model based on IEEE802.11e is analyzed. The quantitative relationship of contention window, backoff counter and retransmission number is revised. Besides, a more accurate normalized terminal throughput expression based on QoS is obtained, and the mentioned model is consummated. Secondly, when designing channel allocation, both the QoS of the communication between the terminals within each BSS and AP and the fairness in overall throughput of the terminals within each AP which associated with it and interfered by adjacent AP channel are considered. Also, modeling analysis of channel interference is adopted and the channel allocation issue is ascribed to an optimization issue. Finally, the optimal channel allocation among AP is obtained by genetic algorithm. Numerical analysis results show, compared with Hsum and Channel Assignment based on the Onder of Throughput Reduction CAOTR algorithms, the proposed Channel Assignment based on Fairness and QoS (CAFQ) algorithm based on generic algorithm can minimize the mutual interference among BSS and make a maximum guarantee of the throughput based on QoS within each BSS. Simultaneously, a relatively good fairness in load balance among BSS is obtained.
Wireless Access Points (APs) deployed in the same hotspot with a high density will cause channel interference. Considering this issue, also combined with the QoS of terminals in the same Basic Service Set (BSS) and the load balance among different BSS, a three-dimensional discrete Markov chain model based on IEEE802.11e is analyzed. The quantitative relationship of contention window, backoff counter and retransmission number is revised. Besides, a more accurate normalized terminal throughput expression based on QoS is obtained, and the mentioned model is consummated. Secondly, when designing channel allocation, both the QoS of the communication between the terminals within each BSS and AP and the fairness in overall throughput of the terminals within each AP which associated with it and interfered by adjacent AP channel are considered. Also, modeling analysis of channel interference is adopted and the channel allocation issue is ascribed to an optimization issue. Finally, the optimal channel allocation among AP is obtained by genetic algorithm. Numerical analysis results show, compared with Hsum and Channel Assignment based on the Onder of Throughput Reduction CAOTR algorithms, the proposed Channel Assignment based on Fairness and QoS (CAFQ) algorithm based on generic algorithm can minimize the mutual interference among BSS and make a maximum guarantee of the throughput based on QoS within each BSS. Simultaneously, a relatively good fairness in load balance among BSS is obtained.
2012, 34(9): 2236-2240.
doi: 10.3724/SP.J.1146.2011.01331
Abstract:
A resource allocation algorithm based on effective capacity theory for downlink multi-service OFDMA systems is proposed, which is focused on the real-time users QoS requirements. A two-dimensional Markov wireless channel model is established, and the radio resources are allocated to real-time users by the adaptive modulation technology, the effective capacity theory and the effective bandwidth theory. The downlink radio resources are also simultaneously allocated to non-real-time and best effort users appropriately. Simulation results show that the proposed algorithm ensures the throughputs of the downlink OFDMA systems, meanwhile, it has some advantages on delay and packet dropping rate of real-time users.
A resource allocation algorithm based on effective capacity theory for downlink multi-service OFDMA systems is proposed, which is focused on the real-time users QoS requirements. A two-dimensional Markov wireless channel model is established, and the radio resources are allocated to real-time users by the adaptive modulation technology, the effective capacity theory and the effective bandwidth theory. The downlink radio resources are also simultaneously allocated to non-real-time and best effort users appropriately. Simulation results show that the proposed algorithm ensures the throughputs of the downlink OFDMA systems, meanwhile, it has some advantages on delay and packet dropping rate of real-time users.
2012, 34(9): 2241-2246.
doi: 10.3724/SP.J.1146.2012.00029
Abstract:
The blind Timing Skews Estimation (TSE) issue for the Time-Interleaved Analog-to-Digital Converters (TIADC) is investigated in this paper. Accordingly to the TIADC configuration, the spectra sparsity of the analog input signal, and the non-overlapping frequency points, the spectra relations among the input signal of the TIADC, the output of the TIADC and the output of the sub-ADCs are explored based on the sampling theorem and the undersampling theory. A novel blind timing skews estimation algorithm is developed by using the phase information of the resultant sequence of the Inverse Discrete Fourier Transform (IDFT) of the relative output spectrum ratio at the non-overlapping frequency point. The simulation results show that the proposed TSE algorithm has the comparable parameter estimation performance of the sin-fit algorithm. Moreover, the proposed algorithm offers some desired properties, such as robustness to the additive noise, no limitation to the frequency of the input signal, no constrains on the channel number of the TIADC and no requirement on oversampling of the input signal. The experimental result using the captured data of a developed TIADC prototype validates further the high accuracy and effectiveness of the proposed TSE algorithm.
The blind Timing Skews Estimation (TSE) issue for the Time-Interleaved Analog-to-Digital Converters (TIADC) is investigated in this paper. Accordingly to the TIADC configuration, the spectra sparsity of the analog input signal, and the non-overlapping frequency points, the spectra relations among the input signal of the TIADC, the output of the TIADC and the output of the sub-ADCs are explored based on the sampling theorem and the undersampling theory. A novel blind timing skews estimation algorithm is developed by using the phase information of the resultant sequence of the Inverse Discrete Fourier Transform (IDFT) of the relative output spectrum ratio at the non-overlapping frequency point. The simulation results show that the proposed TSE algorithm has the comparable parameter estimation performance of the sin-fit algorithm. Moreover, the proposed algorithm offers some desired properties, such as robustness to the additive noise, no limitation to the frequency of the input signal, no constrains on the channel number of the TIADC and no requirement on oversampling of the input signal. The experimental result using the captured data of a developed TIADC prototype validates further the high accuracy and effectiveness of the proposed TSE algorithm.
2012, 34(9): 2247-2253.
doi: 10.3724/SP.J.1146.2012.00048
Abstract:
Through Silicon Via (TSV) is the key technology for vertical interconnections in 3D ICs, with insulator short and bump open being the two major types of TSV defects. In this paper, a TSV defect model is presented and the relationships between the linear oxide resistance/bump resistance and the TSV dimension are discussed. Based on the model, a method is proposed for detecting the voltage of the defects resistance. To verify the proposed method, a self-test circuit which can detect both types of defects is designed, and it can be cascaded to achieve auto-recovery on chip. Then, the area overhead is analyzed and the results show that self-test/recovery circuits will occupy lower percentage of total chip area as CMOS/TSV fabrication technology scales down or as TSV array size increases.
Through Silicon Via (TSV) is the key technology for vertical interconnections in 3D ICs, with insulator short and bump open being the two major types of TSV defects. In this paper, a TSV defect model is presented and the relationships between the linear oxide resistance/bump resistance and the TSV dimension are discussed. Based on the model, a method is proposed for detecting the voltage of the defects resistance. To verify the proposed method, a self-test circuit which can detect both types of defects is designed, and it can be cascaded to achieve auto-recovery on chip. Then, the area overhead is analyzed and the results show that self-test/recovery circuits will occupy lower percentage of total chip area as CMOS/TSV fabrication technology scales down or as TSV array size increases.
2012, 34(9): 2254-2258.
doi: 10.3724/SP.J.1146.2012.00077
Abstract:
This paper presents in-depth research into the system stability of switched-capacitor closed-loop micro- accelerometers. Universal method of dynamic characteristic analysis on such type of micro-accelerometer is imposed. Critical influencing factors of system stability are investigated, including the quality factor of the sensor, the force feedback delay, and the parameters of the electronic compensator. The theory is further confirmed with the design and fabrication of a prototype interface circuit in a commercial 0.35 m CMOS process. Experiment results show that elaborately-designed electronic compensator is very significant for ensuring system stability, while the measured stability border of the system matches well with the theoretic result.
This paper presents in-depth research into the system stability of switched-capacitor closed-loop micro- accelerometers. Universal method of dynamic characteristic analysis on such type of micro-accelerometer is imposed. Critical influencing factors of system stability are investigated, including the quality factor of the sensor, the force feedback delay, and the parameters of the electronic compensator. The theory is further confirmed with the design and fabrication of a prototype interface circuit in a commercial 0.35 m CMOS process. Experiment results show that elaborately-designed electronic compensator is very significant for ensuring system stability, while the measured stability border of the system matches well with the theoretic result.
2012, 34(9): 2259-2262.
doi: 10.3724/SP.J.1146.2011.01023
Abstract:
Zodiac is a block cipher designed by a group of Korean experts. This paper studies the security of Zodiac against the meet-in-the-middle attack for the first time. Some new 9-round and 10-round distinguishers of Zodiac are found, and based on which some meet-in-the-middle attacks are made on 15-round and the full 16-round Zodiac. The results show that the full Zodiac-128/192/256 are not immune to the meet-in-the-middle attack.
Zodiac is a block cipher designed by a group of Korean experts. This paper studies the security of Zodiac against the meet-in-the-middle attack for the first time. Some new 9-round and 10-round distinguishers of Zodiac are found, and based on which some meet-in-the-middle attacks are made on 15-round and the full 16-round Zodiac. The results show that the full Zodiac-128/192/256 are not immune to the meet-in-the-middle attack.
2012, 34(9): 2263-2267.
doi: 10.3724/SP.J.1146.2012.00185
Abstract:
Enhanced SAR ocean images with wind wave signatures and reserved other oceanographic features can promote oceanographic applications. Based on the Goldstein interferogram filter, the enhanced parameter is adaptively determined by the wind wave spectrum power to noise ratio. Meanwhile, the divided wavenumber is determined by SAR imaging parameters and in-suit ocean wind to reserve the low frequency spectrum components. Therefore, the wind wave features are dramatically enhanced and the abundant oceanographic signatures are reserved. Algorithm analysis and experiments show the reasonable efficiency and capabilities.
Enhanced SAR ocean images with wind wave signatures and reserved other oceanographic features can promote oceanographic applications. Based on the Goldstein interferogram filter, the enhanced parameter is adaptively determined by the wind wave spectrum power to noise ratio. Meanwhile, the divided wavenumber is determined by SAR imaging parameters and in-suit ocean wind to reserve the low frequency spectrum components. Therefore, the wind wave features are dramatically enhanced and the abundant oceanographic signatures are reserved. Algorithm analysis and experiments show the reasonable efficiency and capabilities.
2012, 34(9): 2268-2272.
doi: 10.3724/SP.J.1146.2012.00136
Abstract:
It remains a challenging task to restore the image which is contaminated with heavy noise. In this paper, an image denoising method is proposed based on sparse representations. In the dictionary training stage, a matching criterion based on correlation coefficient is introduced and a dictionary pruning scheme is proposed to tackle the conflicting issues of structure extraction and artifact suppression. Experimental results show that the proposed method achieves significant improvements over the previous sparse denoising methods and outperforms the state-of-the-art methods in terms of both objective and subjective quality at high noise level.
It remains a challenging task to restore the image which is contaminated with heavy noise. In this paper, an image denoising method is proposed based on sparse representations. In the dictionary training stage, a matching criterion based on correlation coefficient is introduced and a dictionary pruning scheme is proposed to tackle the conflicting issues of structure extraction and artifact suppression. Experimental results show that the proposed method achieves significant improvements over the previous sparse denoising methods and outperforms the state-of-the-art methods in terms of both objective and subjective quality at high noise level.
2012, 34(9): 2273-2276.
doi: 10.3724/SP.J.1146.2012.00193
Abstract:
In this paper, the linear structure of Rotation Symmetric Boolean Functions (RSBF) is studied. The relationship between the degree and the existence of linear structures in RSBFs is investigated. The open problem that an-variable RSBF being balanced and of degree n-1 has no linear structure except the all-zero vector is proved. A formula for enumerating the self-conjugate orbits is presented. By this formula, the number of RSBFs, which have no linear structure except all-one vectors, is obtained.
In this paper, the linear structure of Rotation Symmetric Boolean Functions (RSBF) is studied. The relationship between the degree and the existence of linear structures in RSBFs is investigated. The open problem that an-variable RSBF being balanced and of degree n-1 has no linear structure except the all-zero vector is proved. A formula for enumerating the self-conjugate orbits is presented. By this formula, the number of RSBFs, which have no linear structure except all-one vectors, is obtained.
2012, 34(9): 2277-2281.
doi: 10.3724/SP.J.1146.2012.00104
Abstract:
ZigBee nodes are deficient in identity authentication and key distribution security. For purpose of solving those issues, an identity-based ZigBee identity authentication and key distribution scheme without weil pairing is proposed. This scheme bears the strongpoint of identity-based authentication scheme. The completion of ZigBee key distribution can be simultaneous with identity authentication implementation with high security and extensibility. Experiments show that the proposed scheme has the advantage of limited storage cost, low energy consumption etc..
ZigBee nodes are deficient in identity authentication and key distribution security. For purpose of solving those issues, an identity-based ZigBee identity authentication and key distribution scheme without weil pairing is proposed. This scheme bears the strongpoint of identity-based authentication scheme. The completion of ZigBee key distribution can be simultaneous with identity authentication implementation with high security and extensibility. Experiments show that the proposed scheme has the advantage of limited storage cost, low energy consumption etc..
2012, 34(9): 2282-2286.
doi: 10.3724/SP.J.1146.2012.00064
Abstract:
Simulation and experiments of the output system for an L-band 10 MW multi-beam klystron are carried out. Parameters of the two-port six-beam coaxial output cavity, such as frequency, quality factor and character impedance, are calculated and analyzed. A output window with a nonstandard flat waveguide is designed, in which two metallic poles are adopted to match the impedance. The VSWR of the window is lower than 1.01 at 1.3 GHz, and the bandwidth is greater than 100 MHz with the (Voltage Standing Wave Ratio) VSWR lower than 1.2. A testing model is manufactured and measured. The experimental results agree well with the design. The beam-wave interaction characteristics of the output cavity are simulated by a 3-D PIC software, and the output radio frequency power is greater than 10 MW with efficiency of more than 65%.
Simulation and experiments of the output system for an L-band 10 MW multi-beam klystron are carried out. Parameters of the two-port six-beam coaxial output cavity, such as frequency, quality factor and character impedance, are calculated and analyzed. A output window with a nonstandard flat waveguide is designed, in which two metallic poles are adopted to match the impedance. The VSWR of the window is lower than 1.01 at 1.3 GHz, and the bandwidth is greater than 100 MHz with the (Voltage Standing Wave Ratio) VSWR lower than 1.2. A testing model is manufactured and measured. The experimental results agree well with the design. The beam-wave interaction characteristics of the output cavity are simulated by a 3-D PIC software, and the output radio frequency power is greater than 10 MW with efficiency of more than 65%.
