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2009 Vol. 31, No. 8
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2009, 31(8): 1779-1785.
doi: 10.3724/SP.J.1146.2009.00057
Abstract:
An adaptive thresholding algorithm for natural image denoising is proposed in this paper, which is based on Stationary Wavelet Transform (SWT) and multiscale products. Different from traditional thresholding denoising algorithm, this threshold is imposed on multiscale products instead of imposed on wavelet coefficients directly. The characteristics of multiscale products of noisy image in SWT domain are analyzed, and an adaptive threshold estimator is proposed. The multiscale products intensify the important structure information of images and weaken the noise, and reach the result of both effective denoising and preserving the edges and details of image simultaneously. Experimental results show that the visual effect and the performance index of proposed algorithm outperform the adaptive multiscale products threshold denoising in dyadic wavelet domain.
An adaptive thresholding algorithm for natural image denoising is proposed in this paper, which is based on Stationary Wavelet Transform (SWT) and multiscale products. Different from traditional thresholding denoising algorithm, this threshold is imposed on multiscale products instead of imposed on wavelet coefficients directly. The characteristics of multiscale products of noisy image in SWT domain are analyzed, and an adaptive threshold estimator is proposed. The multiscale products intensify the important structure information of images and weaken the noise, and reach the result of both effective denoising and preserving the edges and details of image simultaneously. Experimental results show that the visual effect and the performance index of proposed algorithm outperform the adaptive multiscale products threshold denoising in dyadic wavelet domain.
2009, 31(8): 1786-1790.
doi: 10.3724/SP.J.1146.2008.01025
Abstract:
To overcome the limitation of traditional image denoising algorithms, a Novel Nonlinear Image Enhancement Method based on NonSubsampled Contourlet Tansform (NNIEM-NSCT) is proposed in this paper. The method not only preserves the details of image edge but also suppresses the noise by means of an adaptive Bayes shrinkage threshold which takes advantages of the relationship across all subbands in the same level. Secondly, a nonlinear enhancement mapping function is constructed by modifying the NSCT coefficients to change the image enhancement of weak and strong edges efficiently. Experimental results show that the proposed method outperforms the NSCT-based method. The Detail Variance (DV) of proposed method improves about two times more than that of NSCT-based method, when the Background Variance (BV) is almost equal, and a better visual effect is gotten.
To overcome the limitation of traditional image denoising algorithms, a Novel Nonlinear Image Enhancement Method based on NonSubsampled Contourlet Tansform (NNIEM-NSCT) is proposed in this paper. The method not only preserves the details of image edge but also suppresses the noise by means of an adaptive Bayes shrinkage threshold which takes advantages of the relationship across all subbands in the same level. Secondly, a nonlinear enhancement mapping function is constructed by modifying the NSCT coefficients to change the image enhancement of weak and strong edges efficiently. Experimental results show that the proposed method outperforms the NSCT-based method. The Detail Variance (DV) of proposed method improves about two times more than that of NSCT-based method, when the Background Variance (BV) is almost equal, and a better visual effect is gotten.
2009, 31(8): 1791-1795.
doi: 10.3724/SP.J.1146.2008.00595
Abstract:
A novel denoising model for texture images is proposed, which is the soft threshold algorithm depending on both the smoothing parameter in Besov spaces and the scales of wave atoms. This model well considers the good properties of new multiscale geometric analysis toolwave atoms, such as the flexible choice of the orthonormal basis and tight frames, sparse representation of the oscillatory texture images, as well as parabolic scaling between wavelength and the size of the essential support. Numerical experiments show that the proposed model not only has a better denoising performance comparing to the hard and soft threshold, but also significantly improves the SNR with the increase of the smoothing parameter in Besov spaces.
A novel denoising model for texture images is proposed, which is the soft threshold algorithm depending on both the smoothing parameter in Besov spaces and the scales of wave atoms. This model well considers the good properties of new multiscale geometric analysis toolwave atoms, such as the flexible choice of the orthonormal basis and tight frames, sparse representation of the oscillatory texture images, as well as parabolic scaling between wavelength and the size of the essential support. Numerical experiments show that the proposed model not only has a better denoising performance comparing to the hard and soft threshold, but also significantly improves the SNR with the increase of the smoothing parameter in Besov spaces.
2009, 31(8): 1796-1800.
doi: 10.3724/SP.J.1146.2008.00588
Abstract:
A new method which using Gaussian scale mixtures model in the nonsubsampled Contourlet domain is proposed for image denoising. First, a Gaussian scale mixture model is introduced in order to capturing the correlation of nonsubsampled Contourlet locally coefficients. Then the coefficients are estimated by Bayes least squares estimator based on the model. Finally, the inverse nonsubsampled Contourlet transform is applied to the modified coefficients. This arithmetic combines the character of nonsubsampled Contourlet for image edge representation, shift-invariance and the effective of Gaussian scale mixture model for capturing correlation of locally coefficients. The numerical experimental results show the validity of the proposed method.
A new method which using Gaussian scale mixtures model in the nonsubsampled Contourlet domain is proposed for image denoising. First, a Gaussian scale mixture model is introduced in order to capturing the correlation of nonsubsampled Contourlet locally coefficients. Then the coefficients are estimated by Bayes least squares estimator based on the model. Finally, the inverse nonsubsampled Contourlet transform is applied to the modified coefficients. This arithmetic combines the character of nonsubsampled Contourlet for image edge representation, shift-invariance and the effective of Gaussian scale mixture model for capturing correlation of locally coefficients. The numerical experimental results show the validity of the proposed method.
2009, 31(8): 1801-1806.
doi: 10.3724/SP.J.1146.2008.01232
Abstract:
One-dimensional minimum error thresholding method assumes that the histogram distributions of object and background are governed by a mixture Gaussian distribution. Considering the affects of noise and other factors on image quality, based on the assumption of two-dimensional mixture Gaussian distribution, a two-dimensional linear-type minimum error threshold segmentation method is proposed on two-dimensional gray-level histogram. In order to improve the running speed, a fast recursive formula is also given. Experimental results show that the new method is a valuable image segmentation method which can be well adapted to the cases where the variances of the object and the background are distinctly different and contains noises.
One-dimensional minimum error thresholding method assumes that the histogram distributions of object and background are governed by a mixture Gaussian distribution. Considering the affects of noise and other factors on image quality, based on the assumption of two-dimensional mixture Gaussian distribution, a two-dimensional linear-type minimum error threshold segmentation method is proposed on two-dimensional gray-level histogram. In order to improve the running speed, a fast recursive formula is also given. Experimental results show that the new method is a valuable image segmentation method which can be well adapted to the cases where the variances of the object and the background are distinctly different and contains noises.
2009, 31(8): 1807-1811.
doi: 10.3724/SP.J.1146.2008.01150
Abstract:
In this paper, a Multi-Atoms rapid Matching Pursuit (MAMP) algorithm for signal sparse decomposition and its application to image coding are proposed. The MAMP algorithm decompose signal sparsely by selection several atoms at each iteration. A multiscale ridgelet dictionary is constructed and used to represent image based MAMP. The sparsely decomposed data are adaptively quantized and encoded. Experimental results show that the approximation performances of the MAMP algorithm are comparable with those of the matching pursuit. Meanwhile, the computation speed is greatly improved. On the other hand, the performances of the new coding scheme are shown to compare favorably against those of the state of the art JPEG2000 scheme at low bit rate.
In this paper, a Multi-Atoms rapid Matching Pursuit (MAMP) algorithm for signal sparse decomposition and its application to image coding are proposed. The MAMP algorithm decompose signal sparsely by selection several atoms at each iteration. A multiscale ridgelet dictionary is constructed and used to represent image based MAMP. The sparsely decomposed data are adaptively quantized and encoded. Experimental results show that the approximation performances of the MAMP algorithm are comparable with those of the matching pursuit. Meanwhile, the computation speed is greatly improved. On the other hand, the performances of the new coding scheme are shown to compare favorably against those of the state of the art JPEG2000 scheme at low bit rate.
2009, 31(8): 1812-1815.
doi: 10.3724/SP.J.1146.2008.00718
Abstract:
Uncorrelated space algorithm is a fast method for the uncorrelated discriminant vectors extraction，but it may encounter the small size samples problem when it is applied to face recognition task. In addition, it is only a linear feature extraction technique. In this paper，kernel uncorrelated space algorithm is proposed. The key of the proposed algorithm is to how to compute the uncorrelated space in the higher dimensional feature space. As to this problem, a very simple and easy method is proposed, which originates from the eigenface that transforms the computation of the high order matrix into the computation of the low order matrix, and then the actual computation of the uncorrelated space in the higher dimensional feature space is reduced to a standard eignenvalue problem. In addition, the proposed algorithm can effectively overcome small size samples problem. The numerical experiments on facial databases of ORL show that the proposed method is effective and feasible.
Uncorrelated space algorithm is a fast method for the uncorrelated discriminant vectors extraction，but it may encounter the small size samples problem when it is applied to face recognition task. In addition, it is only a linear feature extraction technique. In this paper，kernel uncorrelated space algorithm is proposed. The key of the proposed algorithm is to how to compute the uncorrelated space in the higher dimensional feature space. As to this problem, a very simple and easy method is proposed, which originates from the eigenface that transforms the computation of the high order matrix into the computation of the low order matrix, and then the actual computation of the uncorrelated space in the higher dimensional feature space is reduced to a standard eignenvalue problem. In addition, the proposed algorithm can effectively overcome small size samples problem. The numerical experiments on facial databases of ORL show that the proposed method is effective and feasible.
2009, 31(8): 1816-1820.
doi: 10.3724/SP.J.1146.2008.01094
Abstract:
In this paper, an improved Mean Shift face tracking algorithm based on Local Ternary Patterns (LTP) of texture and color features is proposed to improve the robustness of the Mean Shift algorithm. Based on the study of LTP texture features, an LTP key texture pattern is introduced to enhance the important features of an object and reduce the computational complexity of the LPT texture model. A multiple feature Mean Shift face tracking algorithm is then proposed based on the LTP key texture and complexion features, and the robustness of Mean Shift algorithm is significantly enhanced. Furthermore, in order to improve the tracking speed and robustness, the Kalman filter is introduced to predict the position of the object window. Experimental results show that compared with the original Mean Shift algorithm, the proposed multiple feature face tracking algorithm has significantly improved the tracking performance.
In this paper, an improved Mean Shift face tracking algorithm based on Local Ternary Patterns (LTP) of texture and color features is proposed to improve the robustness of the Mean Shift algorithm. Based on the study of LTP texture features, an LTP key texture pattern is introduced to enhance the important features of an object and reduce the computational complexity of the LPT texture model. A multiple feature Mean Shift face tracking algorithm is then proposed based on the LTP key texture and complexion features, and the robustness of Mean Shift algorithm is significantly enhanced. Furthermore, in order to improve the tracking speed and robustness, the Kalman filter is introduced to predict the position of the object window. Experimental results show that compared with the original Mean Shift algorithm, the proposed multiple feature face tracking algorithm has significantly improved the tracking performance.
2009, 31(8): 1821-1824.
doi: 10.3724/SP.J.1146.2008.01118
Abstract:
A method of spectrum analysis is proposed using recursive least square algorithm to train the weights of Fourier Basis Functions (FBF) neural network. Its main idea is that the weights of the FBF neural network are trained with recursive least square algorithm, and then the amplitude spectrum and phase spectrum are computed according to the obtained weights. The approach is not involved in plural multiplication operation and plural addition operation. Software and hardware of the approach are easily implemented. It is especially fit for the implementation of software and hardware of DSP chips. The results of spectrum analysis show that the method presented has not only high accuracy and fast convergence speed but also filtering function. Therefore, it is an effective approach of spectrum analysis.
A method of spectrum analysis is proposed using recursive least square algorithm to train the weights of Fourier Basis Functions (FBF) neural network. Its main idea is that the weights of the FBF neural network are trained with recursive least square algorithm, and then the amplitude spectrum and phase spectrum are computed according to the obtained weights. The approach is not involved in plural multiplication operation and plural addition operation. Software and hardware of the approach are easily implemented. It is especially fit for the implementation of software and hardware of DSP chips. The results of spectrum analysis show that the method presented has not only high accuracy and fast convergence speed but also filtering function. Therefore, it is an effective approach of spectrum analysis.
2009, 31(8): 1825-1829.
doi: 10.3724/SP.J.1146.2008.01188
Abstract:
Meeting to the need of coherent signal direction-of-arrival estimation, applying particle swarm optimization algorithm, a Generalized Maximum Likelihood algorithm Based on Chaos Adaptive Mutation PSO (CAMPSOGML) optimization is proposed, the arrays geometry is unrestricted, furthermore, the number of sources resolved can be larger than the number of sensors, chaos initiation and adaptive mutation strategy is applied to basic PSO algorithm, the algorithm convergence speed is improved. The PSO algorithms defect which is easy to running into local optimum is overcome. Computer simulation results show that compared with the GML algorithm based on real genetic algorithm (GA) or PSO algorithm, CAMPSOGML algorithm is better at the aspects of convergence speed and estimation accuracy, this algorithm is a new and effective de-correlation DOA algorithm.
Meeting to the need of coherent signal direction-of-arrival estimation, applying particle swarm optimization algorithm, a Generalized Maximum Likelihood algorithm Based on Chaos Adaptive Mutation PSO (CAMPSOGML) optimization is proposed, the arrays geometry is unrestricted, furthermore, the number of sources resolved can be larger than the number of sensors, chaos initiation and adaptive mutation strategy is applied to basic PSO algorithm, the algorithm convergence speed is improved. The PSO algorithms defect which is easy to running into local optimum is overcome. Computer simulation results show that compared with the GML algorithm based on real genetic algorithm (GA) or PSO algorithm, CAMPSOGML algorithm is better at the aspects of convergence speed and estimation accuracy, this algorithm is a new and effective de-correlation DOA algorithm.
2009, 31(8): 1830-1834.
doi: 10.3724/SP.J.1146.2008.01168
Abstract:
To lower the high requirements of both the accuracy of the edge gradient and the integrity of the ellipse, a fast ellipse detection method using only 1-D accumulation array in parameter space based on symmetry points searching is presented to effectively extract multiple unknown ellipses in an image. Three undetermined parameters of the candidate ellipse are determined by the group of the symmetry points which are acquired by random sampling and the validation algorithm based on the ellipse generation and dilation matching is introduced to eliminate the effect of the ellipses distortion on the validation of the candidate ellipses. The experimental results show that compared with the other typical ellipse detection method based on RHT, the method here has the advantage of higher detection speed and accuracy and strong resistance to ellipses partial deletion and distortion.
To lower the high requirements of both the accuracy of the edge gradient and the integrity of the ellipse, a fast ellipse detection method using only 1-D accumulation array in parameter space based on symmetry points searching is presented to effectively extract multiple unknown ellipses in an image. Three undetermined parameters of the candidate ellipse are determined by the group of the symmetry points which are acquired by random sampling and the validation algorithm based on the ellipse generation and dilation matching is introduced to eliminate the effect of the ellipses distortion on the validation of the candidate ellipses. The experimental results show that compared with the other typical ellipse detection method based on RHT, the method here has the advantage of higher detection speed and accuracy and strong resistance to ellipses partial deletion and distortion.
2009, 31(8): 1835-1839.
doi: 10.3724/SP.J.1146.2008.01217
Abstract:
It is difficult to get effective group member matching by their position or attribute measurement separately when the sensors position measurement noise level is high and their identification performance is relatively poor or the members types are not exclusive. So a matching algorithm for group members measurement is given which synthesizes their position and attribute information. The matching belief functions related to the position and attribute measurement respectively are constructed which are further combined with a newly defined combination rule. Besides, a new matching decision idea is proposed which is based on the truncation of the measurement sequence. Simulation experiments validate the effectiveness of the proposed algorithm.
It is difficult to get effective group member matching by their position or attribute measurement separately when the sensors position measurement noise level is high and their identification performance is relatively poor or the members types are not exclusive. So a matching algorithm for group members measurement is given which synthesizes their position and attribute information. The matching belief functions related to the position and attribute measurement respectively are constructed which are further combined with a newly defined combination rule. Besides, a new matching decision idea is proposed which is based on the truncation of the measurement sequence. Simulation experiments validate the effectiveness of the proposed algorithm.
2009, 31(8): 1840-1845.
doi: 10.3724/SP.J.1146.2008.00946
Abstract:
Supervised Locality Preserving Projection (SLPP) is a generalization of Locality Preserving Projection (LPP) in the case of supervised learning. In this paper the drawback of SLPP in the high-dimensional and small sample size case is pointed out, and a new algorithm called Generalized Supervised Locality Preserving Projection (GSLPP) is proposed. The relationship between SLPP and GSLPP is theoretically analyzed. In the small sample size case GSLPP can be solved equivalently in lower-dimensionality space. Finally, the effectiveness of the proposed algorithm is verified by experimental results.
Supervised Locality Preserving Projection (SLPP) is a generalization of Locality Preserving Projection (LPP) in the case of supervised learning. In this paper the drawback of SLPP in the high-dimensional and small sample size case is pointed out, and a new algorithm called Generalized Supervised Locality Preserving Projection (GSLPP) is proposed. The relationship between SLPP and GSLPP is theoretically analyzed. In the small sample size case GSLPP can be solved equivalently in lower-dimensionality space. Finally, the effectiveness of the proposed algorithm is verified by experimental results.
2009, 31(8): 1846-1851.
doi: 10.3724/SP.J.1146.2008.00959
Abstract:
A modified flocking model with virtual leaders is proposed, and then a clustering algorithm based on it is developed. In the algorithm, firstly a weighted and undirected graph is established by all data points in a dataset according to the model, where each data point is regarded as an agent who can move in space. Then a set of virtual leaders are identified, from whichvirtual leaders are chosen and linked by each data point. Furthermore, each data point is acted by all linked data points through fields established by them in space, so it will take a step along the direction of the vector sum of all fields. Thanks to those virtual leaders, they accelerate the rate of convergence of the algorithm. As all data points move in space according to the proposed model, data points that belong to the same class are located at a same position, whereas those that belong to other classes are away from one another. Consequently, the experimental results demonstrate that data points in datasets are clustered reasonably and efficiently, and in several iterations the convergence of the algorithm will be reached. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of proposed approach.
A modified flocking model with virtual leaders is proposed, and then a clustering algorithm based on it is developed. In the algorithm, firstly a weighted and undirected graph is established by all data points in a dataset according to the model, where each data point is regarded as an agent who can move in space. Then a set of virtual leaders are identified, from whichvirtual leaders are chosen and linked by each data point. Furthermore, each data point is acted by all linked data points through fields established by them in space, so it will take a step along the direction of the vector sum of all fields. Thanks to those virtual leaders, they accelerate the rate of convergence of the algorithm. As all data points move in space according to the proposed model, data points that belong to the same class are located at a same position, whereas those that belong to other classes are away from one another. Consequently, the experimental results demonstrate that data points in datasets are clustered reasonably and efficiently, and in several iterations the convergence of the algorithm will be reached. Moreover, the comparison with other algorithms also provides an indication of the effectiveness of proposed approach.
2009, 31(8): 1852-1855.
doi: 10.3724/SP.J.1146.2008.01215
Abstract:
This paper proposes one new method of integrating intuitionistic fuzzy conditional reasoning with conditional entropy based on the hypothesis of an equilibrium state of supportability and opposability of neutral evidences indicated in the intuitionistic index. The first component and last component as conditional attributes and decision attributes in decision and information system is considered. For conditional attributes, decision attributes and decision rules all can be treated as intuitionistic fuzzy propositions, the confidence degree of intuitionistic fuzzy propositions is measured by conditional entropy. At the same time, the range of conditional entropy, which demonstrates the confidence degree of intuitionistic fuzzy propositions is also calculated.
This paper proposes one new method of integrating intuitionistic fuzzy conditional reasoning with conditional entropy based on the hypothesis of an equilibrium state of supportability and opposability of neutral evidences indicated in the intuitionistic index. The first component and last component as conditional attributes and decision attributes in decision and information system is considered. For conditional attributes, decision attributes and decision rules all can be treated as intuitionistic fuzzy propositions, the confidence degree of intuitionistic fuzzy propositions is measured by conditional entropy. At the same time, the range of conditional entropy, which demonstrates the confidence degree of intuitionistic fuzzy propositions is also calculated.
2009, 31(8): 1856-1861.
doi: 10.3724/SP.J.1146.2008.00966
Abstract:
In this paper, an improved 2D Fourier domain simulator is presented, which can take the effects of baseline oscillations into account accurately. The phase error caused by baseline oscillation is separated into the azimuth time-variant term and the range space-variant one by Taylor expansion and then is taken into account accurately. The analysis of validity limits shows that this algorithm can be used for the simulation of practical systems. It is accurate and efficient, so it has good application values.
In this paper, an improved 2D Fourier domain simulator is presented, which can take the effects of baseline oscillations into account accurately. The phase error caused by baseline oscillation is separated into the azimuth time-variant term and the range space-variant one by Taylor expansion and then is taken into account accurately. The analysis of validity limits shows that this algorithm can be used for the simulation of practical systems. It is accurate and efficient, so it has good application values.
2009, 31(8): 1862-1866.
doi: 10.3724/SP.J.1146.2008.01218
Abstract:
A new method of SAR jamming is proposed: the 2-D cosinusoidal phase modulation repeater jamming. This jamming method makes SAR echo extend both in range frequency domain and azimuth?Doppler domain via 2-D cosinusoidal phase modulation, and achieves the effect of multi-false targets. The research in principle shows: this jamming takes advantages of both efficient energy usage like 2-D coherent jamming and well suppression as non-coherent jamming. It can form tight flat shape false targets or grid shape false targets to protect distributed important targets, according to well configured jamming modulation parameters. Its validities are proved by the simulation and real data simulation.
A new method of SAR jamming is proposed: the 2-D cosinusoidal phase modulation repeater jamming. This jamming method makes SAR echo extend both in range frequency domain and azimuth?Doppler domain via 2-D cosinusoidal phase modulation, and achieves the effect of multi-false targets. The research in principle shows: this jamming takes advantages of both efficient energy usage like 2-D coherent jamming and well suppression as non-coherent jamming. It can form tight flat shape false targets or grid shape false targets to protect distributed important targets, according to well configured jamming modulation parameters. Its validities are proved by the simulation and real data simulation.
2009, 31(8): 1867-1871.
doi: 10.3724/SP.J.1146.2008.00745
Abstract:
In subarray level phased array, it requires digital beam scanning at subarray level in many applications, for instance, multiple beamforming. In this case, the suppression of pattern sidelobe is critical, and the key is construction of the weighting network at subarray level. This paper considers the whole array as a super array and each subarray as a super element. Based on the concept adopting super element patterns to express approximately original subarray patterns, the dimension of each matrix which is required for constructing weighting network could reduce to the same value as subarray numbers of the array compared to the original value equaling to element numbers. Consequently, the computation cost is remarkably reduced. And all the obtained new subarray patterns are quite similar in forms, widths and gains of mainbeams. For subarray level beam scanning, the proposed approach could reduce sidelobe of array pattern to certain extent. Simulation results demonstrate its validity.
In subarray level phased array, it requires digital beam scanning at subarray level in many applications, for instance, multiple beamforming. In this case, the suppression of pattern sidelobe is critical, and the key is construction of the weighting network at subarray level. This paper considers the whole array as a super array and each subarray as a super element. Based on the concept adopting super element patterns to express approximately original subarray patterns, the dimension of each matrix which is required for constructing weighting network could reduce to the same value as subarray numbers of the array compared to the original value equaling to element numbers. Consequently, the computation cost is remarkably reduced. And all the obtained new subarray patterns are quite similar in forms, widths and gains of mainbeams. For subarray level beam scanning, the proposed approach could reduce sidelobe of array pattern to certain extent. Simulation results demonstrate its validity.
2009, 31(8): 1872-1875.
doi: 10.3724/SP.J.1146.2008.01097
Abstract:
To solve the problem of too much time spending on calculating the distribution of radar detection range over sea, firstly ,the method characteristic of calculating radar detection range in condition of evaporation duct is described, the influence of evaporation duct height, the bulk Richardson number and wind speed on radar detection range is presented, then consulting table method based on this influence is advised to use for calculating radar detection range of each weather record over sea and the principle of constructing standard radar detection range table is outlined. The calculating time is greatly shorten by means of consulting table method, the result difference between consulting table method and that of direct calculation is small, so this method can meet the requirement of summarizing the distribution of radar detection range over sea quickly.
To solve the problem of too much time spending on calculating the distribution of radar detection range over sea, firstly ,the method characteristic of calculating radar detection range in condition of evaporation duct is described, the influence of evaporation duct height, the bulk Richardson number and wind speed on radar detection range is presented, then consulting table method based on this influence is advised to use for calculating radar detection range of each weather record over sea and the principle of constructing standard radar detection range table is outlined. The calculating time is greatly shorten by means of consulting table method, the result difference between consulting table method and that of direct calculation is small, so this method can meet the requirement of summarizing the distribution of radar detection range over sea quickly.
2009, 31(8): 1876-1880.
doi: 10.3724/SP.J.1146.2008.00241
Abstract:
The method of moving target detection based on eigen-decomposition of the covariance matrix is proposed for single-antenna airborne SAR. First the paper points out that the sub-image is obtained through frequency processing. The imaging difference of sub-images as the result of the sub-aperture division is rectified using the adaptive 2D-calibration. The magnitude and phase difference can be corrected at the same time and the sub-images like the multi-channel can be obtained. Then the developed method combines the concept of multi-channel samples covariance matrix. The fundament of the separation between clutter and moving target based on the decomposition of the sub-image sample covariance matrix is analyzed. The estimation of the sample covariance matrix in image brings the inconsistency between the accuracy and the decrease of the targets energy. The improved method of estimation is calculated in range-doppler domain is proposed and the moving target is indicated based on the second eigenvalues. Simulation results demonstrate that the method is effective.
The method of moving target detection based on eigen-decomposition of the covariance matrix is proposed for single-antenna airborne SAR. First the paper points out that the sub-image is obtained through frequency processing. The imaging difference of sub-images as the result of the sub-aperture division is rectified using the adaptive 2D-calibration. The magnitude and phase difference can be corrected at the same time and the sub-images like the multi-channel can be obtained. Then the developed method combines the concept of multi-channel samples covariance matrix. The fundament of the separation between clutter and moving target based on the decomposition of the sub-image sample covariance matrix is analyzed. The estimation of the sample covariance matrix in image brings the inconsistency between the accuracy and the decrease of the targets energy. The improved method of estimation is calculated in range-doppler domain is proposed and the moving target is indicated based on the second eigenvalues. Simulation results demonstrate that the method is effective.
2009, 31(8): 1881-1885.
doi: 10.3724/SP.J.1146.2008.01705
Abstract:
Based on Fractional Fourier Transform (FrFT) and clutter suppression interferometer techniques, a method of detecting slow-moving ground targets with Geosynchronous Earth Orbit (GEO) spaceborne-airborne bistatic three-aperture Synthetic Aperture Radar (SAR) is presented. Firstly, based on the characteristic of GEO spaceborne-airborne bistatic SAR, the DPCA condition of clutter suppression is derived. Then from the spatial geometry model and echo signal of the system, the theory of moving target focusing, clutter suppression, moving target detection and parameter estimation is derived in detail. Finally, computer simulation results validate its effectiveness.
Based on Fractional Fourier Transform (FrFT) and clutter suppression interferometer techniques, a method of detecting slow-moving ground targets with Geosynchronous Earth Orbit (GEO) spaceborne-airborne bistatic three-aperture Synthetic Aperture Radar (SAR) is presented. Firstly, based on the characteristic of GEO spaceborne-airborne bistatic SAR, the DPCA condition of clutter suppression is derived. Then from the spatial geometry model and echo signal of the system, the theory of moving target focusing, clutter suppression, moving target detection and parameter estimation is derived in detail. Finally, computer simulation results validate its effectiveness.
2009, 31(8): 1886-1891.
doi: 10.3724/SP.J.1146.2008.01123
Abstract:
Since the sidelobe suppression of a random signal is a difficulty in research, it has realistic meaning to suppress the sidelobe in a simple and effective way. A continuous time model of random frequency modulation signal is developed in this paper. The root mean square bandwidth and point spread function of the random frequency modulation signal both in gaussian and uniform distribution cases are investigated theoretically. The signal model is verified by the result of the simulation, which shows that it can obtain a higher Peak SideLobe Ratio(PSLR) that the linear frequency modulation case, and it can achieve a good effectersult in radar imaging.
Since the sidelobe suppression of a random signal is a difficulty in research, it has realistic meaning to suppress the sidelobe in a simple and effective way. A continuous time model of random frequency modulation signal is developed in this paper. The root mean square bandwidth and point spread function of the random frequency modulation signal both in gaussian and uniform distribution cases are investigated theoretically. The signal model is verified by the result of the simulation, which shows that it can obtain a higher Peak SideLobe Ratio(PSLR) that the linear frequency modulation case, and it can achieve a good effectersult in radar imaging.
2009, 31(8): 1892-1897.
doi: 10.3724/SP.J.1146.2008.01181
Abstract:
A feature vector extraction method to the envelope function in rotation angledomain of radar signals based on FRFT is proposed in this paper, because extracting the novel radar signal parameters is an effective method to solve the complex radar emitter signals sorting and radar target recognition problem. This method searches the envelope function ofdomain through FRFT firstly, extractsvalue corresponding of the peak, peak value and kurtosis of the envelope function to construct a new feature vector as the complement to classical parameters. At the same time, a dynamic cluster sorting method is used to complete the sorting work to radar emitters. A large number of simulation results show that, the new feature vector not only has strong compactness within clusters and large separation between clusters, but also has good anti-noise performance. And the results verify the feasibility and effectiveness of this new feature vector as the complement to classical parameters.
A feature vector extraction method to the envelope function in rotation angledomain of radar signals based on FRFT is proposed in this paper, because extracting the novel radar signal parameters is an effective method to solve the complex radar emitter signals sorting and radar target recognition problem. This method searches the envelope function ofdomain through FRFT firstly, extractsvalue corresponding of the peak, peak value and kurtosis of the envelope function to construct a new feature vector as the complement to classical parameters. At the same time, a dynamic cluster sorting method is used to complete the sorting work to radar emitters. A large number of simulation results show that, the new feature vector not only has strong compactness within clusters and large separation between clusters, but also has good anti-noise performance. And the results verify the feasibility and effectiveness of this new feature vector as the complement to classical parameters.
2009, 31(8): 1898-1902.
doi: 10.3724/SP.J.1146.2008.01023
Abstract:
In this paper, the characteristic of FRFT modules about LFM signal and monochromatic signal is researched. Based on this characteristic, two new methods based on difference of FRFT modules for moving target detection are proposed. One is based on difference of FRFT modules of echo signal and its time-lapse signal. The other is based on difference of FRFT modules with two symmetry inverse rotation angles of echo signal, and one of the FRFT modules has been overturned. In these methods, sea clutter is suppressed effectively. SCR can be improved to some extent, and the detection performance is good in low SCR. Finally, simulation results show the effectivity of proposed methods.
In this paper, the characteristic of FRFT modules about LFM signal and monochromatic signal is researched. Based on this characteristic, two new methods based on difference of FRFT modules for moving target detection are proposed. One is based on difference of FRFT modules of echo signal and its time-lapse signal. The other is based on difference of FRFT modules with two symmetry inverse rotation angles of echo signal, and one of the FRFT modules has been overturned. In these methods, sea clutter is suppressed effectively. SCR can be improved to some extent, and the detection performance is good in low SCR. Finally, simulation results show the effectivity of proposed methods.
2009, 31(8): 1903-1907.
doi: 10.3724/SP.J.1146.2008.01027
Abstract:
In order to improve the anti-interference performance and system capacity of cognitive Frequency Hopping Code Division Multiple Access (FH-CDMA) communication systems, a kind of time-frequency sequence with three no hit zone, which can be made reconfiguration based on cognitive collaboration, is presented by this paper. The sequence design method is proved effectively. A construction example is enumerated, as well as the performance of its Hamming correlation function is explained. This kind of construction method of time-frequency sequences can be made reconfiguration and applied highly in cognitive reconfigurable communication systems.
In order to improve the anti-interference performance and system capacity of cognitive Frequency Hopping Code Division Multiple Access (FH-CDMA) communication systems, a kind of time-frequency sequence with three no hit zone, which can be made reconfiguration based on cognitive collaboration, is presented by this paper. The sequence design method is proved effectively. A construction example is enumerated, as well as the performance of its Hamming correlation function is explained. This kind of construction method of time-frequency sequences can be made reconfiguration and applied highly in cognitive reconfigurable communication systems.
2009, 31(8): 1908-1913.
doi: 10.3724/SP.J.1146.2008.01063
Abstract:
In this paper, a practicable user traffic satisfaction evaluation model of the VoIP traffic and the real-time video traffic is proposed. This method calculates the users traffic quality of experience according to the packet loss rate and the packet loss pattern measured in MAC layer. Using the proposed traffic satisfaction evaluation criterion, a satisfaction based packet scheduling and resource allocation algorithm is proposed. The simulation results show that, the proposed algorithm can provide better traffic satisfaction to users while keeping a high system throughput.
In this paper, a practicable user traffic satisfaction evaluation model of the VoIP traffic and the real-time video traffic is proposed. This method calculates the users traffic quality of experience according to the packet loss rate and the packet loss pattern measured in MAC layer. Using the proposed traffic satisfaction evaluation criterion, a satisfaction based packet scheduling and resource allocation algorithm is proposed. The simulation results show that, the proposed algorithm can provide better traffic satisfaction to users while keeping a high system throughput.
2009, 31(8): 1914-1918.
doi: 10.3724/SP.J.1146.2008.01200
Abstract:
In this paper, an iterative precoding method is proposed, which successively in turn optimizes the precoding matrix at base station or relay station for suppressing the multiuser interference of multiuser multi-relay MIMO system. Firstly, the multi-relay joint zero forcing precoding is adopted at relay station. Secondly, the channel between the base station and multiple users is taken as an equivalent point-to-multipoint MIMO channel, then the signal-to-leakage ratio precoding method at base station is used to further cancel inter-user interference and avoid the Influence of noise amplification. Furthermore, Multiple iterative precoding at relay stations and base station can maintain better space diversity introduced by parallel transmission of multiple relays, also can achieve higher sum capacity of system.
In this paper, an iterative precoding method is proposed, which successively in turn optimizes the precoding matrix at base station or relay station for suppressing the multiuser interference of multiuser multi-relay MIMO system. Firstly, the multi-relay joint zero forcing precoding is adopted at relay station. Secondly, the channel between the base station and multiple users is taken as an equivalent point-to-multipoint MIMO channel, then the signal-to-leakage ratio precoding method at base station is used to further cancel inter-user interference and avoid the Influence of noise amplification. Furthermore, Multiple iterative precoding at relay stations and base station can maintain better space diversity introduced by parallel transmission of multiple relays, also can achieve higher sum capacity of system.
2009, 31(8): 1919-1924.
doi: 10.3724/SP.J.1146.2008.01127
Abstract:
In this paper, the power control problem is studied for secondary users to share primary users spectrum. The joint power and rate control under minimal-maximal fair criterion is formulated as a quasi-concave optimization, and an algorithm is proposed to obtain the optimal solution by iteratively solving linear programmings. Moreover, an approach is presented to estimate the link gains used in power control, the statistics of estimation error is analyzed, and the safeguard margins are used to alleviate the impact of the estimation error on the quality of service (QoS) of primary users and secondary users. Simulation results show that the proposed algorithm reduces the computation time by 50%~90% or more without performance loss, and that 1 dB interference margin and 1.5 dB signal-to-interference and noise margin are enough to guarantee the QoS of both primary and secondary users in the presence of the link gain estimation error, respectively.
In this paper, the power control problem is studied for secondary users to share primary users spectrum. The joint power and rate control under minimal-maximal fair criterion is formulated as a quasi-concave optimization, and an algorithm is proposed to obtain the optimal solution by iteratively solving linear programmings. Moreover, an approach is presented to estimate the link gains used in power control, the statistics of estimation error is analyzed, and the safeguard margins are used to alleviate the impact of the estimation error on the quality of service (QoS) of primary users and secondary users. Simulation results show that the proposed algorithm reduces the computation time by 50%~90% or more without performance loss, and that 1 dB interference margin and 1.5 dB signal-to-interference and noise margin are enough to guarantee the QoS of both primary and secondary users in the presence of the link gain estimation error, respectively.
2009, 31(8): 1925-1929.
doi: 10.3724/SP.J.1146.2008.01154
Abstract:
Spectrum sharing of Cognitive Radios (CRs) has broad application prospects to the new generation of wireless communication networks. In multi-cognitive-user circumstance, using tools from asymptotic random matrix theory, a new cooperative scheme for frequency band sensing is proposed. The property of asymptotic spectrum distribution of random matrices and the convergence of the maximum eigenvalue with low samples are well considered. Theoretical analysis and simulations results show that the new algorithm is obviously outperforming congener algorithms and classical energy detection techniques.
Spectrum sharing of Cognitive Radios (CRs) has broad application prospects to the new generation of wireless communication networks. In multi-cognitive-user circumstance, using tools from asymptotic random matrix theory, a new cooperative scheme for frequency band sensing is proposed. The property of asymptotic spectrum distribution of random matrices and the convergence of the maximum eigenvalue with low samples are well considered. Theoretical analysis and simulations results show that the new algorithm is obviously outperforming congener algorithms and classical energy detection techniques.
2009, 31(8): 1930-1934.
doi: 10.3724/SP.J.1146.2008.00856
Abstract:
Adopting the hybrid MLSE (H-MLSE) on each MISO subsystem firstly, and then combining the -selection of survival states, a complexity-controllable sequence detention method with adaptive channel tracking is proposed for Multi-Input Multi-Output (MIMO) time-varying multipath channels. In contrast to the conventional MLSE, the proposed method has three features: (1) the adjustable computational complexity, which can be achieved by adjusting the parameter; (2) the on-line channel tracking with near zero-delay, which is embedded in the scheme and accomplished for each selected survival state transition along the corresponding path by decision-directed/LMS algorithm (DD/LMS); (3) It can be partly implemented by parallel processing technology. The simulation results show the proposed method can achieve the satisfactory detection performance for 2X4 time-varying MIMO channel with two multipaths when 2.
Adopting the hybrid MLSE (H-MLSE) on each MISO subsystem firstly, and then combining the -selection of survival states, a complexity-controllable sequence detention method with adaptive channel tracking is proposed for Multi-Input Multi-Output (MIMO) time-varying multipath channels. In contrast to the conventional MLSE, the proposed method has three features: (1) the adjustable computational complexity, which can be achieved by adjusting the parameter; (2) the on-line channel tracking with near zero-delay, which is embedded in the scheme and accomplished for each selected survival state transition along the corresponding path by decision-directed/LMS algorithm (DD/LMS); (3) It can be partly implemented by parallel processing technology. The simulation results show the proposed method can achieve the satisfactory detection performance for 2X4 time-varying MIMO channel with two multipaths when 2.
2009, 31(8): 1935-1940.
doi: 10.3724/SP.J.1146.2008.00700
Abstract:
Dynamic resource allocation algorithms are investigated for multi-cell Orthogonal Frequency Division Multiple Access (OFDMA) systems based on noncooperative game theory where the maximal power of each Base Station (BS) is assigned equally to all subcarriers and all BSs operate noncooperative user scheduling and resource allocation game at each subcarrier independently. Firstly, a joint noncooperative game framework is proposed for user scheduling and power allocation. Secondly, to simplify further, the whole procedure is divided into two steps where a noncooperative power allocation game model is formulated by introducing channel gain of each scheduled user into its pricing function. Thirdly, the existence and uniqueness of Nash equilibrium of the proposed game model are analyzed. Finally, a specific algorithm is developed accordingly. Simulation results demonstrate that the proposed algorithm improves system level fairness with good performance in terms of system throughput.
Dynamic resource allocation algorithms are investigated for multi-cell Orthogonal Frequency Division Multiple Access (OFDMA) systems based on noncooperative game theory where the maximal power of each Base Station (BS) is assigned equally to all subcarriers and all BSs operate noncooperative user scheduling and resource allocation game at each subcarrier independently. Firstly, a joint noncooperative game framework is proposed for user scheduling and power allocation. Secondly, to simplify further, the whole procedure is divided into two steps where a noncooperative power allocation game model is formulated by introducing channel gain of each scheduled user into its pricing function. Thirdly, the existence and uniqueness of Nash equilibrium of the proposed game model are analyzed. Finally, a specific algorithm is developed accordingly. Simulation results demonstrate that the proposed algorithm improves system level fairness with good performance in terms of system throughput.
2009, 31(8): 1941-1945.
doi: 10.3724/SP.J.1146.2008.01213
Abstract:
In multi-user multi-antenna downlink system, when the channels are Rician channels, the performance of those limited feedback strategies designed for uncorrelated Rayleigh Channels will result to the waste of feedback overhead. To solve this problem, a new adaptive feedback strategy is proposed in Rician channels. First, a new concept of the angle distance distribution in the Rician channel is introduced. Based on this theory and using the channel mean information at the transmitter, the proposed strategy can design a special threshold to adjust users codebook, which is closer to the channel direction. Moreover, this strategy can still adjust its number of feedback bits adaptively according to different channel distributions without increasing the quantized error of channel direction. The simulation shows that, compared to those strategies proposed for Rayleigh systems, the strategy can reduce feedback overhead greatly without decreasing system sum-rate.
In multi-user multi-antenna downlink system, when the channels are Rician channels, the performance of those limited feedback strategies designed for uncorrelated Rayleigh Channels will result to the waste of feedback overhead. To solve this problem, a new adaptive feedback strategy is proposed in Rician channels. First, a new concept of the angle distance distribution in the Rician channel is introduced. Based on this theory and using the channel mean information at the transmitter, the proposed strategy can design a special threshold to adjust users codebook, which is closer to the channel direction. Moreover, this strategy can still adjust its number of feedback bits adaptively according to different channel distributions without increasing the quantized error of channel direction. The simulation shows that, compared to those strategies proposed for Rayleigh systems, the strategy can reduce feedback overhead greatly without decreasing system sum-rate.
2009, 31(8): 1946-1951.
doi: 10.3724/SP.J.1146.2008.01120
Abstract:
In order to design a low-computational Time Of Arrival (TOA) estimation algorithm for the Ultra WideBand (UWB) based wireless sensor network, a new TOA estimation method which focuses on the Direct Path (DP) component based on weighted energy detection is proposed in this paper. This method includes two steps, one is DP energy block detection, and the other is the refined DP estimation. A closed form for performance analysis is proposed, and system parameters that affect estimation performance are studied with analytical and numerical methods. The results compared with traditional ranging methods also show that this method can achieve relative high performance under low sample rate conditions.
In order to design a low-computational Time Of Arrival (TOA) estimation algorithm for the Ultra WideBand (UWB) based wireless sensor network, a new TOA estimation method which focuses on the Direct Path (DP) component based on weighted energy detection is proposed in this paper. This method includes two steps, one is DP energy block detection, and the other is the refined DP estimation. A closed form for performance analysis is proposed, and system parameters that affect estimation performance are studied with analytical and numerical methods. The results compared with traditional ranging methods also show that this method can achieve relative high performance under low sample rate conditions.
2009, 31(8): 1952-1956.
doi: 10.3724/SP.J.1146.2008.00923
Abstract:
The spread-spectrum system usually works in the multipath environment, along with the additive noise there always be some multiplicative noise. In order to solve the pseudonoise (PN) code acquisition in multiplicative noise channel, a new detector is proposed in this paper. Modeling the acquisition problem as a hypothesis testing problem, a detector is derived for multiplicative noise, based on the locally optimum detection technique. Numerical results show that the proposed detector can offer substantial performance improvement over the conventional schemes in multiplicative noise channels.
The spread-spectrum system usually works in the multipath environment, along with the additive noise there always be some multiplicative noise. In order to solve the pseudonoise (PN) code acquisition in multiplicative noise channel, a new detector is proposed in this paper. Modeling the acquisition problem as a hypothesis testing problem, a detector is derived for multiplicative noise, based on the locally optimum detection technique. Numerical results show that the proposed detector can offer substantial performance improvement over the conventional schemes in multiplicative noise channels.
2009, 31(8): 1957-1960.
doi: 10.3724/SP.J.1146.2008.01280
Abstract:
To enable the practicability of the low density parity check codes, a QCE-PEG algorithm is presented, followed by the description of the implementation approach and a design case in detail. The algorithm divides the construction into two processes, combining the Quasi-Cyclic Extension (QCE) method and Progressive Edge-Growth (PEG) technique. It has several advantages such as good degree distribution, long average girth, rapid encoding process and good performance. Simulation result shows that the constructed irregular LDPC codes have good performance, simple and practicable, thus creating good conditions for its wider application.
To enable the practicability of the low density parity check codes, a QCE-PEG algorithm is presented, followed by the description of the implementation approach and a design case in detail. The algorithm divides the construction into two processes, combining the Quasi-Cyclic Extension (QCE) method and Progressive Edge-Growth (PEG) technique. It has several advantages such as good degree distribution, long average girth, rapid encoding process and good performance. Simulation result shows that the constructed irregular LDPC codes have good performance, simple and practicable, thus creating good conditions for its wider application.
2009, 31(8): 1961-1964.
doi: 10.3724/SP.J.1146.2007.02019
Abstract:
For the high power amplifier pedistorter using memory polynomial, a novel fractional order memory polynomial predistorter is proposed. The proposed predistortion polynomial is achieved by changing the even order term to fractional order term in the memory polynomial predistorter to improve the linearization performance. Computer simulations show that the proposed polynomial predistorter can get 10 dB and 8 dB out-band suppression gain based on two typical polynomial predistorters for Wiener-Hammerstein and memory polynomial power amplifier. FPGA realization shows that its increasing cost of hardware resources is acceptable, so easiness to implemented.
For the high power amplifier pedistorter using memory polynomial, a novel fractional order memory polynomial predistorter is proposed. The proposed predistortion polynomial is achieved by changing the even order term to fractional order term in the memory polynomial predistorter to improve the linearization performance. Computer simulations show that the proposed polynomial predistorter can get 10 dB and 8 dB out-band suppression gain based on two typical polynomial predistorters for Wiener-Hammerstein and memory polynomial power amplifier. FPGA realization shows that its increasing cost of hardware resources is acceptable, so easiness to implemented.
2009, 31(8): 1965-1968.
doi: 10.3724/SP.J.1146.2008.01149
Abstract:
In this paper, two novel methods called EAIC (Extended Active Interference Cancellation) and EAIC-H (EAIC-Hybrid) for spectral sculpting of OFDM signal are proposed. In EAIC and EAIC-H, cancellation signals are added to OFDM signal to cancel interference in target spectrum band caused by data tones, so that interference perceived by primary user can be limited. The cancellation signal (EAIC tones) has longer time duration than that of OFDM symbol, which enables a better notching capability than that of most existing methods. Simulation results show that the proposed methods can obtain very deep spectral notches of about 80 dB. Compared with EAIC, EAIC-H provides a better tradeoff between notching performance and SNR degradation for high order modulation.
In this paper, two novel methods called EAIC (Extended Active Interference Cancellation) and EAIC-H (EAIC-Hybrid) for spectral sculpting of OFDM signal are proposed. In EAIC and EAIC-H, cancellation signals are added to OFDM signal to cancel interference in target spectrum band caused by data tones, so that interference perceived by primary user can be limited. The cancellation signal (EAIC tones) has longer time duration than that of OFDM symbol, which enables a better notching capability than that of most existing methods. Simulation results show that the proposed methods can obtain very deep spectral notches of about 80 dB. Compared with EAIC, EAIC-H provides a better tradeoff between notching performance and SNR degradation for high order modulation.
2009, 31(8): 1969-1974.
doi: 10.3724/SP.J.1146.2008.00991
Abstract:
In the service invocation mechanism of current IMS (IP Multimedia System) network, the Serving-Call Session Control Function (S-CSCF) invokes each Application Server (AS) sequentially to perform users service profile. This mechanism makes SIP request be forwarded excessively among the S-CSCF and Application Servers (ASs), so it is easy to result in the heavy load of the S-CSCF entity and long call set-up delay. This paper proposes a novel Distributed SCIM (DSCIM) service invocation mechanism. It aims at reducing the call set-up delay in IMS service layer along with decreasing the load of the S-CSCF entity by invoking each AS consecutively without signaling being forwarded back to the S-CSCF. The service invocation mechanisms are modeled through Jackson network and the simulations of different scenarios verify that DSCIM service invocation mechanism can effectively reduce call set-up delay of the network and decrease the load level of the S-CSCF.
In the service invocation mechanism of current IMS (IP Multimedia System) network, the Serving-Call Session Control Function (S-CSCF) invokes each Application Server (AS) sequentially to perform users service profile. This mechanism makes SIP request be forwarded excessively among the S-CSCF and Application Servers (ASs), so it is easy to result in the heavy load of the S-CSCF entity and long call set-up delay. This paper proposes a novel Distributed SCIM (DSCIM) service invocation mechanism. It aims at reducing the call set-up delay in IMS service layer along with decreasing the load of the S-CSCF entity by invoking each AS consecutively without signaling being forwarded back to the S-CSCF. The service invocation mechanisms are modeled through Jackson network and the simulations of different scenarios verify that DSCIM service invocation mechanism can effectively reduce call set-up delay of the network and decrease the load level of the S-CSCF.
2009, 31(8): 1975-1979.
doi: 10.3724/SP.J.1146.2008.01162
Abstract:
In this paper, a Dynamic Layered-Graph(DLG) routing model based on Cognitive Radio(CR) mesh networks is proposed .The channel which Cognitive Radio node can sense is modeled by a two states discrete time Markov chain and a model depict Cognitive Radio networks topology and connectivity is built up. A cross-layer design dynamic interface assignment policy is also proposed based on the model. Simulation results show that as the aspect of the adaptability of the dynamic access spectrum and depicting the topology of Cognitive Radio Mesh networks, the performance of Dynamic Layered-Graph model outperforms the Static Layered-Graph(SLG) model.
In this paper, a Dynamic Layered-Graph(DLG) routing model based on Cognitive Radio(CR) mesh networks is proposed .The channel which Cognitive Radio node can sense is modeled by a two states discrete time Markov chain and a model depict Cognitive Radio networks topology and connectivity is built up. A cross-layer design dynamic interface assignment policy is also proposed based on the model. Simulation results show that as the aspect of the adaptability of the dynamic access spectrum and depicting the topology of Cognitive Radio Mesh networks, the performance of Dynamic Layered-Graph model outperforms the Static Layered-Graph(SLG) model.
2009, 31(8): 1980-1984.
doi: 10.3724/SP.J.1146.2008.01138
Abstract:
In interconnect modeling, an exact original model is needed, whether in considering frequency-dependent or process variation or in model reducing. An exact original model is not only a precise start-point in model reducing, but also is the basis of evaluating the performance of the reduction models. This paper presents three types of exact interconnect RLGC state space models in time domain with super high order and computation complexity of O(N) by closed forms, where N is the total system order. They are the fundamental elements to construct interconnect trees or a special interconnect tree. The forms of these models are simpler than which in literature. Low order models are compared with 2000th order model. Low order models cause quite big errors in respect of the descriptions of oscillation characteristic and rise time. It has a risk when modeling branches in interconnect trees using lower order original interconnect models.
In interconnect modeling, an exact original model is needed, whether in considering frequency-dependent or process variation or in model reducing. An exact original model is not only a precise start-point in model reducing, but also is the basis of evaluating the performance of the reduction models. This paper presents three types of exact interconnect RLGC state space models in time domain with super high order and computation complexity of O(N) by closed forms, where N is the total system order. They are the fundamental elements to construct interconnect trees or a special interconnect tree. The forms of these models are simpler than which in literature. Low order models are compared with 2000th order model. Low order models cause quite big errors in respect of the descriptions of oscillation characteristic and rise time. It has a risk when modeling branches in interconnect trees using lower order original interconnect models.
2009, 31(8): 1996-2000.
doi: 10.3724/SP.J.1146.2008.01152
Abstract:
In multisensor tracking systems that operate in a centralized manner, there are usually different time delays in transmitting the scans or frames from the various sensors to the center. This can lead to situations where measurements from the same target arrive out of sequence. Thus, such Out-Of-Sequence Measurement (OOSM) problem is result in. Inherited from the idea of reconstruction of Centralized Estimate, a new algorithm for out of sequence measurement problem, by fusing forward prediction and equivalent measurement approach, is presented. The algorithm involves a decorrelation problem. Theoretical Analysis and Monte Carlo Simulation results indicate that the new algorithm corresponding to the 1-step lag OOSM case is optimal, and when the process noise is small, and/or the update rate of system tracks is reasonably high, the degradation in performance of the algorithm has been shown to be small.
In multisensor tracking systems that operate in a centralized manner, there are usually different time delays in transmitting the scans or frames from the various sensors to the center. This can lead to situations where measurements from the same target arrive out of sequence. Thus, such Out-Of-Sequence Measurement (OOSM) problem is result in. Inherited from the idea of reconstruction of Centralized Estimate, a new algorithm for out of sequence measurement problem, by fusing forward prediction and equivalent measurement approach, is presented. The algorithm involves a decorrelation problem. Theoretical Analysis and Monte Carlo Simulation results indicate that the new algorithm corresponding to the 1-step lag OOSM case is optimal, and when the process noise is small, and/or the update rate of system tracks is reasonably high, the degradation in performance of the algorithm has been shown to be small.
2009, 31(8): 2001-2005.
doi: 10.3724/SP.J.1146.2008.01209
Abstract:
The Ultra-WideBand Through-Wall Radar (UWB TWR) has become a keen research topic in recent years because of the urgent needs of counter-terrorism and calamity rescue, etc. Conventional UWB imaging algorithm can not meet the demand in the capability of targets recognition and calculation efficiency. The Shape Estimation Algorithm based on the Boundary scattering transform and Extraction of Directly scattered waves (SEABED) can be used to reconstruct target shape, but it is restricted by the presence of the wall in the application of TWR. In this paper, a novel envelop curve algorithm is presented to adapt to the special conditions in TWR. To realize imaging of the target boundary, the algorithm extracts the quasi wavefront from the received signals and computes the envelop curve of a group of circles. FDTD numerical simulations validate that the algorithm can be used to obtain two-dimensional images of targets behind walls. The position error by the influence of the walls is also analyzed.
The Ultra-WideBand Through-Wall Radar (UWB TWR) has become a keen research topic in recent years because of the urgent needs of counter-terrorism and calamity rescue, etc. Conventional UWB imaging algorithm can not meet the demand in the capability of targets recognition and calculation efficiency. The Shape Estimation Algorithm based on the Boundary scattering transform and Extraction of Directly scattered waves (SEABED) can be used to reconstruct target shape, but it is restricted by the presence of the wall in the application of TWR. In this paper, a novel envelop curve algorithm is presented to adapt to the special conditions in TWR. To realize imaging of the target boundary, the algorithm extracts the quasi wavefront from the received signals and computes the envelop curve of a group of circles. FDTD numerical simulations validate that the algorithm can be used to obtain two-dimensional images of targets behind walls. The position error by the influence of the walls is also analyzed.
2009, 31(8): 2006-2010.
doi: 10.3724/SP.J.1146.2008.01015
Abstract:
A dynamic multi-frequency digital lock-in algorithm is presented in this paper. By this algorithm, the amplitude of the signal composed of the fundamental and the harmonics can be obtained. And in addition, the problem of frequency drift is solved by rectifying the reference frequency dynamically. Compared with the traditional method, this novel algorithm uses more information and does not need to choose the reference signal. When applied to NDIR gas concentration measurement, it not only widens the measurement range, but also improves the sensitivity of the detection.
A dynamic multi-frequency digital lock-in algorithm is presented in this paper. By this algorithm, the amplitude of the signal composed of the fundamental and the harmonics can be obtained. And in addition, the problem of frequency drift is solved by rectifying the reference frequency dynamically. Compared with the traditional method, this novel algorithm uses more information and does not need to choose the reference signal. When applied to NDIR gas concentration measurement, it not only widens the measurement range, but also improves the sensitivity of the detection.
2009, 31(8): 2011-2014.
doi: 10.3724/SP.J.1146.2008.01052
Abstract:
Based on EXIT chart and APSO algorithm, a new method to optimize the degree distributions of irregular LDPC codes is proposed in this paper. An overall cost function is first designed to measure the matching extent of EXIT curves. Then the degree distributions are optimized iteratively by using the Adaptive Particle Swarm Optimizer (APSO) algorithm. Such a procedure needs not to fasten the Check Nodes Decoder(CND) curve. And therefore, some new degree distributions with higher noise threshold are obtained. Simulation results show that APSO-EXIT algorithm has a good performance to achieve optimal code structures, and it is more effective than Gaussian Approximation in computation.
Based on EXIT chart and APSO algorithm, a new method to optimize the degree distributions of irregular LDPC codes is proposed in this paper. An overall cost function is first designed to measure the matching extent of EXIT curves. Then the degree distributions are optimized iteratively by using the Adaptive Particle Swarm Optimizer (APSO) algorithm. Such a procedure needs not to fasten the Check Nodes Decoder(CND) curve. And therefore, some new degree distributions with higher noise threshold are obtained. Simulation results show that APSO-EXIT algorithm has a good performance to achieve optimal code structures, and it is more effective than Gaussian Approximation in computation.
2009, 31(8): 2015-2018.
doi: 10.3724/SP.J.1146.2008.01185
Abstract:
Multimedia encryption algorithms are widely studied in recent years. However, the performances of those algorithms are usually checked by qualitative analysis and simulations. In this paper, the compression performance of a sort of encryption algorithms for binary image is analyzed quantitatively using information theories. It shows that those algorithms are good at performances including security, speed, compression ratio, robustness and format-compliance, and therefore suitable for practical use.
Multimedia encryption algorithms are widely studied in recent years. However, the performances of those algorithms are usually checked by qualitative analysis and simulations. In this paper, the compression performance of a sort of encryption algorithms for binary image is analyzed quantitatively using information theories. It shows that those algorithms are good at performances including security, speed, compression ratio, robustness and format-compliance, and therefore suitable for practical use.
2009, 31(8): 2019-2023.
doi: 10.3724/SP.J.1146.2008.00960
Abstract:
A cross-layer transmission and scheduling scheme of average power minimization in cognitive radio networks under the constraint of packet drop probability is addressed. The scheme is formulated by constrained Markov Decision Process (MDP). Lagrangian multiplier approach is used to solve the MDP, and a golden section search method is proposed to find the multiplier. Two simplifying methods, namely, state aggregate and action set reduction are employed to cope with the curse of dimensionality. Simulation results show that simplifying methods have little influence on the performance of the scheme and average power consumption of the scheme is the lowest.
A cross-layer transmission and scheduling scheme of average power minimization in cognitive radio networks under the constraint of packet drop probability is addressed. The scheme is formulated by constrained Markov Decision Process (MDP). Lagrangian multiplier approach is used to solve the MDP, and a golden section search method is proposed to find the multiplier. Two simplifying methods, namely, state aggregate and action set reduction are employed to cope with the curse of dimensionality. Simulation results show that simplifying methods have little influence on the performance of the scheme and average power consumption of the scheme is the lowest.
2009, 31(8): 2024-2027.
doi: 10.3724/SP.J.1146.2008.01169
Abstract:
A transmit diversity scheme, called Labelled Delay Space-Time Spreading (LDSTS) is proposed for communication systems in underwater acoustic(UWA) channels with propagation delays and multipath spreading. The scheme eliminates the propagation delays and multipath delays by using the channel probe signals, transmitted in sequence and Rake receivers. The signals are transmitted from transducers in sequence enable the scheme is practice for applications to UWA communication system. The signal models are proposed and BER performances of the scheme with FSK and PSK modulation are analyzed. Simulations results show that the scheme realizes complement transmit diversity gains in multipath UWA channel.
A transmit diversity scheme, called Labelled Delay Space-Time Spreading (LDSTS) is proposed for communication systems in underwater acoustic(UWA) channels with propagation delays and multipath spreading. The scheme eliminates the propagation delays and multipath delays by using the channel probe signals, transmitted in sequence and Rake receivers. The signals are transmitted from transducers in sequence enable the scheme is practice for applications to UWA communication system. The signal models are proposed and BER performances of the scheme with FSK and PSK modulation are analyzed. Simulations results show that the scheme realizes complement transmit diversity gains in multipath UWA channel.
2009, 31(8): 2028-2032.
doi: 10.3724/SP.J.1146.2008.01128
Abstract:
Searching for files in popular unstructured P2P file-sharing systems contributes to much of internet traffic. While existing mechanisms can locate popular files easily, studies show they fail to find rare files exiting in the system. In fact the benefit users obtained from rare resources is not less than popular resources. So high searching hit for rare resources will dramatically improve the whole P2P networks practicability. This paper proposes a simple distributed mechanism-NLIR which makes it easy to find rare files as well as popular files. According to peers heterogeneity, it distributes rare files index replications uniformly into the networks. Even with constraint conditions that bandwidth and storage is limited, it can achieve high hit-rate for rare resources. Both analysis and simulations demonstrate it improves the performance of the system.
Searching for files in popular unstructured P2P file-sharing systems contributes to much of internet traffic. While existing mechanisms can locate popular files easily, studies show they fail to find rare files exiting in the system. In fact the benefit users obtained from rare resources is not less than popular resources. So high searching hit for rare resources will dramatically improve the whole P2P networks practicability. This paper proposes a simple distributed mechanism-NLIR which makes it easy to find rare files as well as popular files. According to peers heterogeneity, it distributes rare files index replications uniformly into the networks. Even with constraint conditions that bandwidth and storage is limited, it can achieve high hit-rate for rare resources. Both analysis and simulations demonstrate it improves the performance of the system.
2009, 31(8): 1985-1989.
doi: 10.3724/SP.J.1146.2008.01026
Abstract:
To verify the high spectral efficiency of VWDK, the principle of the modulation is introduced in detail. The simulation results of VWDK modulation and demodulation confirm that UNB is not what is generally called. Moreover, through calculating the analytic formula of its power spectrum, and analyzing the distribution of its spectra power, the so called high spectral efficiency of VWDK is just an illusion.
To verify the high spectral efficiency of VWDK, the principle of the modulation is introduced in detail. The simulation results of VWDK modulation and demodulation confirm that UNB is not what is generally called. Moreover, through calculating the analytic formula of its power spectrum, and analyzing the distribution of its spectra power, the so called high spectral efficiency of VWDK is just an illusion.
2009, 31(8): 1990-1995.
doi: 10.3724/SP.J.1146.2008.01202
Abstract:
Key derivation is an essential part of key agreement protocol. In 2007, Wang et al. presented an identity-based authenticated key agreement protocol in standard model. However there exists serious fault in key derivation of the protocol. In this paper, key derivation phase in standard model is subdivided into randomness extraction and key derivation. And a new authenticated key agreement protocol is devised using identity-based encryption scheme introduced by Kiltz et al, which has a tightly security reduction and performance efficiency.
Key derivation is an essential part of key agreement protocol. In 2007, Wang et al. presented an identity-based authenticated key agreement protocol in standard model. However there exists serious fault in key derivation of the protocol. In this paper, key derivation phase in standard model is subdivided into randomness extraction and key derivation. And a new authenticated key agreement protocol is devised using identity-based encryption scheme introduced by Kiltz et al, which has a tightly security reduction and performance efficiency.
