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2014 Vol. 36, No. 7
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2014, 36(7): 1525-1531.
doi: 10.3724/SP.J.1146.2013.01338
Abstract:
By taking into account of the prior information of the sparse signal and the additive noise encountered in the measurement process, the sparse recover algorithm under the Bayesian framework can reconstruct the coefficient better. However, the traditional Sparse Bayesian Learning (SBL) algorithm holds many parameters and its timeliness is poor. In this paper, a new sparse Bayesian learning algorithm named Expansion-Compression Variance- component based method (ExCoV) is considered, which only endows a different variance-component to the significant signal elements. Unlikely, the SBL has a distinct variance component on the all signal elements. In addition, the ExCoV has much less parameters than the SBL. Combined with the Compress Sensing (CS) theory, the ExCoV is used in the ISAR imaging model under the Computerized Tomography (CT) frame, and its applicability and the imaging quality are compared with the Polar Format Algorithm (PFA), Convolution Back Projection Algorithm (CBPA) and the traditional sparse recover algorithm. The point scatter simulation verifies that the Inverse SAR (ISAR) image obtained by the ExCoV has low sidelobe and high resolution, and is not sensitive to noise. The imaging results of real data show that the ExCoV has more sparse ISAR image, indicating that it is a more effective and potential ISAR imaging algorithm.
By taking into account of the prior information of the sparse signal and the additive noise encountered in the measurement process, the sparse recover algorithm under the Bayesian framework can reconstruct the coefficient better. However, the traditional Sparse Bayesian Learning (SBL) algorithm holds many parameters and its timeliness is poor. In this paper, a new sparse Bayesian learning algorithm named Expansion-Compression Variance- component based method (ExCoV) is considered, which only endows a different variance-component to the significant signal elements. Unlikely, the SBL has a distinct variance component on the all signal elements. In addition, the ExCoV has much less parameters than the SBL. Combined with the Compress Sensing (CS) theory, the ExCoV is used in the ISAR imaging model under the Computerized Tomography (CT) frame, and its applicability and the imaging quality are compared with the Polar Format Algorithm (PFA), Convolution Back Projection Algorithm (CBPA) and the traditional sparse recover algorithm. The point scatter simulation verifies that the Inverse SAR (ISAR) image obtained by the ExCoV has low sidelobe and high resolution, and is not sensitive to noise. The imaging results of real data show that the ExCoV has more sparse ISAR image, indicating that it is a more effective and potential ISAR imaging algorithm.
2014, 36(7): 1532-1537.
doi: 10.3724/SP.J.1146.2013.01419
Abstract:
The target shape imaging algorithms receive great attention in applications of Ultra WideBand Through Wall (UWB-TW) radar, because it overcomes the shortcomings of real-time imaging and image quality in traditional Back Projection (BP) imaging algorithms. The classical SEABED and Envelope algorithms are typical target shape imaging algorithms, which have still some defects such as poor anti-noise capability and imaging accuracy. This paper presents a target shape imaging algorithm with the envelope of ellipses for the bistatic UWB-TW radar. The ellipse model regarding a target boundary is established by analyzing the geometry relationship between the target boundary and the coordinates of antennas. With this model, the target boundary can be expressed as a boundary of a union and an intersection set of these ellipses to achieve the target shape imaging, which derives from their mapping relationship. The results of numerical simulations and experiments show that the proposed algorithm can improve the imaging accuracy and the capability of anti-noise, leading to the better performance of through-wall imaging.
The target shape imaging algorithms receive great attention in applications of Ultra WideBand Through Wall (UWB-TW) radar, because it overcomes the shortcomings of real-time imaging and image quality in traditional Back Projection (BP) imaging algorithms. The classical SEABED and Envelope algorithms are typical target shape imaging algorithms, which have still some defects such as poor anti-noise capability and imaging accuracy. This paper presents a target shape imaging algorithm with the envelope of ellipses for the bistatic UWB-TW radar. The ellipse model regarding a target boundary is established by analyzing the geometry relationship between the target boundary and the coordinates of antennas. With this model, the target boundary can be expressed as a boundary of a union and an intersection set of these ellipses to achieve the target shape imaging, which derives from their mapping relationship. The results of numerical simulations and experiments show that the proposed algorithm can improve the imaging accuracy and the capability of anti-noise, leading to the better performance of through-wall imaging.
2014, 36(7): 1538-1544.
doi: 10.3724/SP.J.1146.2013.01310
Abstract:
Under the effects of the initial perturbation and torque, the motion of the spin-stability spacecraft is the compound of nutation and precession, named quasi-regularized precession. The motion parameters estimation of the quasi-regularized precession object is important to the determination of the attitude and the reentry point of the object. This paper presents a novel method to estimate the motion parameters of the rotation symmetric object based on the measurements from wideband radar. Firstly, the kinematic model of the quasi-regularized precession is derived; and then the algorithm of 3D motion reconstruction from 1D radial range histories of multiple scatterers is extended to the 2D motion reconstruction of the rotation symmetric object; and thirdly based on the 2D Euclidian motion reconstruction result, the method of nutation and precession parameters estimation is proposed by using the cyclic iterative of sequential quadratic programming and nonlinear least square algorithm. The electromagnetic simulated data show that the proposed method is validated for its effectiveness.
Under the effects of the initial perturbation and torque, the motion of the spin-stability spacecraft is the compound of nutation and precession, named quasi-regularized precession. The motion parameters estimation of the quasi-regularized precession object is important to the determination of the attitude and the reentry point of the object. This paper presents a novel method to estimate the motion parameters of the rotation symmetric object based on the measurements from wideband radar. Firstly, the kinematic model of the quasi-regularized precession is derived; and then the algorithm of 3D motion reconstruction from 1D radial range histories of multiple scatterers is extended to the 2D motion reconstruction of the rotation symmetric object; and thirdly based on the 2D Euclidian motion reconstruction result, the method of nutation and precession parameters estimation is proposed by using the cyclic iterative of sequential quadratic programming and nonlinear least square algorithm. The electromagnetic simulated data show that the proposed method is validated for its effectiveness.
2014, 36(7): 1545-1551.
doi: 10.3724/SP.J.1146.2013.01046
Abstract:
The existing vector weighted robust beamforming is able to estimate the signal power of target only in situations of a small steering angle error. For a larger steering angle error case, although the matrix weighted beamforming can effectively estimate the signal power of the target as well, the system implementation is more complicated than above mentioned vector weighted. In order to solve these problems, this paper presents a new robust beamforming approach based on SemiDefinite rank Relaxation (SDR). Detailed description of the proposed method are given as follows: the optimal model has the same objective as that of the Capon algorithm; the optimization variable is the covariance matrix of weight vector with constraints posed on the ripple of mainlobe amplitude and sidelobe level, and the rank of covariance matrix is 1; the covariance matrix of the weight vector can be obtained by the SDR method, and each row or column of the matrix is translated into weight vector, then a weight vector is chosen which allows it become minimal one in the maximum distortions between the mainlobe of beampattern and 0 dB. The system implementation complexity of the proposed method is the same as the vector weighted methods, and the signal power estimation performance is similar to the matrix weighted method. The simulation results show that the desired beampattern shape and effective estimation of signal power can be obtained under the condition that the large steering angle error exists.
The existing vector weighted robust beamforming is able to estimate the signal power of target only in situations of a small steering angle error. For a larger steering angle error case, although the matrix weighted beamforming can effectively estimate the signal power of the target as well, the system implementation is more complicated than above mentioned vector weighted. In order to solve these problems, this paper presents a new robust beamforming approach based on SemiDefinite rank Relaxation (SDR). Detailed description of the proposed method are given as follows: the optimal model has the same objective as that of the Capon algorithm; the optimization variable is the covariance matrix of weight vector with constraints posed on the ripple of mainlobe amplitude and sidelobe level, and the rank of covariance matrix is 1; the covariance matrix of the weight vector can be obtained by the SDR method, and each row or column of the matrix is translated into weight vector, then a weight vector is chosen which allows it become minimal one in the maximum distortions between the mainlobe of beampattern and 0 dB. The system implementation complexity of the proposed method is the same as the vector weighted methods, and the signal power estimation performance is similar to the matrix weighted method. The simulation results show that the desired beampattern shape and effective estimation of signal power can be obtained under the condition that the large steering angle error exists.
2014, 36(7): 1552-1559.
doi: 10.3724/SP.J.1146.2013.01739
Abstract:
The deceptive mainlobe jamming of airborne radar not only causes a large amount of false alarms but also contaminates samples of the Space-Time Adaptive Processor (STAP). Hence, the performance on clutter suppression is degraded and signal self-cancellation occurs due to the distorted adaptive pattern. A polarization-space adaptive beamforming algorithm utilizing the polarization difference between the target signal and jamming is proposed for suppressing the deceptive mainlobe jamming. Firstly, the eigen-fusion based jamming covariance matrix is estimated by the samples obtained from clutter-free Doppler zone. Then, the polarization-space adaptive beamforming algorithm is carried out via synthesizing subarrays with overlapped window. This algorithm has the ability to suppress mainlobe jamming and retain the spatial degree of freedom for clutter suppression. Finally, the STAP is utilized to suppress the residual clutter. The proposed method can efficiently suppress the dense deceptive jamming, and hence, reduce the number of false alarms. The performance of STAP for clutter suppression can also be improved. Simulation results verify the effectiveness of the proposed method.
The deceptive mainlobe jamming of airborne radar not only causes a large amount of false alarms but also contaminates samples of the Space-Time Adaptive Processor (STAP). Hence, the performance on clutter suppression is degraded and signal self-cancellation occurs due to the distorted adaptive pattern. A polarization-space adaptive beamforming algorithm utilizing the polarization difference between the target signal and jamming is proposed for suppressing the deceptive mainlobe jamming. Firstly, the eigen-fusion based jamming covariance matrix is estimated by the samples obtained from clutter-free Doppler zone. Then, the polarization-space adaptive beamforming algorithm is carried out via synthesizing subarrays with overlapped window. This algorithm has the ability to suppress mainlobe jamming and retain the spatial degree of freedom for clutter suppression. Finally, the STAP is utilized to suppress the residual clutter. The proposed method can efficiently suppress the dense deceptive jamming, and hence, reduce the number of false alarms. The performance of STAP for clutter suppression can also be improved. Simulation results verify the effectiveness of the proposed method.
2014, 36(7): 1560-1565.
doi: 10.3724/SP.J.1146.2013.01258
Abstract:
Considering the urgent need of high precision motion parameter for SAR motion compensation in real-time, a motion compensation scheme using the Strapdown Inertial Navigation System/Global Positioning System (SINS/GPS) integrated system based on Rauch-Tung-Striebel (R-T-S) smoothing method is proposed. In this scheme, the Kalman filtering is done firstly and based on this, the backward smoothing iteration is performed for correcting the filters results during each synthetic aperture moment. The results of numerical simulation and flight-test data processing show that the scheme can effectively improve the precision of estimates of the motion parameter in the synthetic aperture moment.
Considering the urgent need of high precision motion parameter for SAR motion compensation in real-time, a motion compensation scheme using the Strapdown Inertial Navigation System/Global Positioning System (SINS/GPS) integrated system based on Rauch-Tung-Striebel (R-T-S) smoothing method is proposed. In this scheme, the Kalman filtering is done firstly and based on this, the backward smoothing iteration is performed for correcting the filters results during each synthetic aperture moment. The results of numerical simulation and flight-test data processing show that the scheme can effectively improve the precision of estimates of the motion parameter in the synthetic aperture moment.
2014, 36(7): 1566-1572.
doi: 10.3724/SP.J.1146.2013.00822
Abstract:
The mission of imaging is usually not considered in existing resource scheduling strategies of phased array radar, and it is required to separate a fixed part of resources for target imaging. In this paper, the concept of cognitive imaging is introduced to the radar resource scheduling strategy, and then a novel adaptive scheduling algorithm is proposed based on sparse-aperture cognitive Inverse Synthetic Aperture Radar (ISAR) imaging. The corresponding performance evaluation indicators of the proposed algorithm are also given. Based on the cognition of targets characteristics, the time resource of radar can be allocated adaptively according to the feedback information, and then the cognitive imaging of targets is achieved simultaneously during implementing tracking and searching tasks. As a result, the efficiency of the radar is improved significantly. Simulation results validate the effectiveness of the proposed algorithm.
The mission of imaging is usually not considered in existing resource scheduling strategies of phased array radar, and it is required to separate a fixed part of resources for target imaging. In this paper, the concept of cognitive imaging is introduced to the radar resource scheduling strategy, and then a novel adaptive scheduling algorithm is proposed based on sparse-aperture cognitive Inverse Synthetic Aperture Radar (ISAR) imaging. The corresponding performance evaluation indicators of the proposed algorithm are also given. Based on the cognition of targets characteristics, the time resource of radar can be allocated adaptively according to the feedback information, and then the cognitive imaging of targets is achieved simultaneously during implementing tracking and searching tasks. As a result, the efficiency of the radar is improved significantly. Simulation results validate the effectiveness of the proposed algorithm.
2014, 36(7): 1573-1578.
doi: 10.3724/SP.J.1146.2013.01123
Abstract:
An angle estimation algorithm based on fourth-order cumulants for distributed targets in monostatic Multiple Input Multiple Output (MIMO) radar is proposed in this paper, which could be used to deal with the problem of the performance declining in colored noise based on second order statics algorithm. At first, the signal model of coherent distributed targets is constructed, and then the fourth-order cumulants matrix can be calculated. Based on the eigen-decomposition, the signal subspace and the noise subspace, which are orthogonal, can be derived. Finally, according to the principle of the MUltiple SIgnal Classification (MUSIC), the spectral function can be obtained, and with spectral peak searching, the central direction of arrival is estimated. The proposed algorithm makes full use of the property of fourth-order cumulants which ignores the Gaussian process to restrain the influence of the colored noise on estimating the angles. The computer simulation results demonstrate the correction and efficiency of the proposed method.
An angle estimation algorithm based on fourth-order cumulants for distributed targets in monostatic Multiple Input Multiple Output (MIMO) radar is proposed in this paper, which could be used to deal with the problem of the performance declining in colored noise based on second order statics algorithm. At first, the signal model of coherent distributed targets is constructed, and then the fourth-order cumulants matrix can be calculated. Based on the eigen-decomposition, the signal subspace and the noise subspace, which are orthogonal, can be derived. Finally, according to the principle of the MUltiple SIgnal Classification (MUSIC), the spectral function can be obtained, and with spectral peak searching, the central direction of arrival is estimated. The proposed algorithm makes full use of the property of fourth-order cumulants which ignores the Gaussian process to restrain the influence of the colored noise on estimating the angles. The computer simulation results demonstrate the correction and efficiency of the proposed method.
2014, 36(7): 1579-1584.
doi: 10.3724/SP.J.1146.2013.01474
Abstract:
Based on the relationship between the velocities of 2D motion and the pose angle, a pose angle aided target tracking algorithm is proposed. In terms of target kinematics, the tracking models, in which the state vector includes pose information, are constructed to realize the aiding for target tracking. In order to improve the filtering ability of nonlinear non-Gaussian systems, the Gaussian Sum Square-root Cubature Kalman Filter (GSSCKF) algorithm is proposed by introducing Square-root Cubature Kalman Filter (SCKF) into the framework of Gaussian Sum Filter (GSF), due to the non-Gaussian pose measurement noise obtained by model matching. Moreover, tracking models with different pose components are established by exploiting the pose variation law in targets motion, and maneuvering pose is estimated by model switching. The proposed algorithm is able not only to filter the pose measurement, but also to fuse the pose information and the position information effectively. The simulation results show the validity and the correctnesss of the proposed algorithm.
Based on the relationship between the velocities of 2D motion and the pose angle, a pose angle aided target tracking algorithm is proposed. In terms of target kinematics, the tracking models, in which the state vector includes pose information, are constructed to realize the aiding for target tracking. In order to improve the filtering ability of nonlinear non-Gaussian systems, the Gaussian Sum Square-root Cubature Kalman Filter (GSSCKF) algorithm is proposed by introducing Square-root Cubature Kalman Filter (SCKF) into the framework of Gaussian Sum Filter (GSF), due to the non-Gaussian pose measurement noise obtained by model matching. Moreover, tracking models with different pose components are established by exploiting the pose variation law in targets motion, and maneuvering pose is estimated by model switching. The proposed algorithm is able not only to filter the pose measurement, but also to fuse the pose information and the position information effectively. The simulation results show the validity and the correctnesss of the proposed algorithm.
2014, 36(7): 1585-1591.
doi: 10.3724/SP.J.1146.2013.00715
Abstract:
A systematic review of the phase error of the conventional airborne InSAR data processing method is firstly presented, which is caused by the center-beam approximation, and the unknown terrain, and its effects on imaging quality and height accuracy are analyzed as well. Then, a novel airborne InSAR data processing method based on the BP algorithm and the time-varying baseline is proposed for addressing the center-beam approximation problem and reducing the height error due to the unknown terrain which have been both accomplished. Finally, the validity of the proposed method is testified by the simulation experiments.
A systematic review of the phase error of the conventional airborne InSAR data processing method is firstly presented, which is caused by the center-beam approximation, and the unknown terrain, and its effects on imaging quality and height accuracy are analyzed as well. Then, a novel airborne InSAR data processing method based on the BP algorithm and the time-varying baseline is proposed for addressing the center-beam approximation problem and reducing the height error due to the unknown terrain which have been both accomplished. Finally, the validity of the proposed method is testified by the simulation experiments.
2014, 36(7): 1592-1598.
doi: 10.3724/SP.J.1146.2013.01317
Abstract:
The sub-system composed of an element of the receiver array and the transmitter in Synthetic Aperture Sonar (SAS) is studied. Due to the double square rooted terms in the slant range history of the sub-system, the fourth-order Taylor expansion is used to approximate the slant range. Then, the system transfer function in two-dimensional frequency domain is derived via series reversion and the method of stationary phase. Based on that, a new Range-Doppler (R-D) imaging algorithm applied to long receiver array and wide beam cases is proposed. With the presented method, the echo signals corresponding to each sub-system are processed firstly. Next, a high resolution SAS complex image can be obtained by coherently superposing each individual image. The simulation and real datasets demonstrate the validity of the proposed method.
The sub-system composed of an element of the receiver array and the transmitter in Synthetic Aperture Sonar (SAS) is studied. Due to the double square rooted terms in the slant range history of the sub-system, the fourth-order Taylor expansion is used to approximate the slant range. Then, the system transfer function in two-dimensional frequency domain is derived via series reversion and the method of stationary phase. Based on that, a new Range-Doppler (R-D) imaging algorithm applied to long receiver array and wide beam cases is proposed. With the presented method, the echo signals corresponding to each sub-system are processed firstly. Next, a high resolution SAS complex image can be obtained by coherently superposing each individual image. The simulation and real datasets demonstrate the validity of the proposed method.
2014, 36(7): 1599-1604.
doi: 10.3724/SP.J.1146.2013.01330
Abstract:
The performance of direction finding of traditional MUltiple SIgnal Classification (MUSIC) method decreases sharply in the presence of sensor mutual coupling. In order to estimate effectively Mutual Coupling Matrix (MCM) of array and Direction Of Arrival (DOA) of incident signals, a cascade estimation method of MCM combined with DOA is proposed. Based on the structural features of MCM, DOA and MCM are decoupled by converting array manifold. By solving a quadratic optimization problem under the linear constraint and utilizing peak search technology to obtain DOA and MCM, the mutual coupling errors can be self-calibrated. The effectiveness and superiority of the proposed algorithm are verified by the computational simulation results.
The performance of direction finding of traditional MUltiple SIgnal Classification (MUSIC) method decreases sharply in the presence of sensor mutual coupling. In order to estimate effectively Mutual Coupling Matrix (MCM) of array and Direction Of Arrival (DOA) of incident signals, a cascade estimation method of MCM combined with DOA is proposed. Based on the structural features of MCM, DOA and MCM are decoupled by converting array manifold. By solving a quadratic optimization problem under the linear constraint and utilizing peak search technology to obtain DOA and MCM, the mutual coupling errors can be self-calibrated. The effectiveness and superiority of the proposed algorithm are verified by the computational simulation results.
2014, 36(7): 1605-1611.
doi: 10.3724/SP.J.1146.2013.01358
Abstract:
Recently, a class of tracking techniques called tracking by detection receive much attention in computer vision. These methods train a discriminative classsifier to separate the object from the background. The classifier bootstraps itself by using the current tracker state to extract positive and negative examples from the current frame. Slight inaccuracies in the tracker lead to incorrectly labeled training examples, which degrade the classifier and cause drift. In this paper, an effective algorithm is proposed to overcome the target drift. It takes the framework of tracking by detection. Median Flow (MF) is used as a tracker to improve the reliability of the tracking point; the detector is constituted with several weak classifiers of random ferns to cascade, and it is updated with online Multiple Instance Learning (MIL). Finally the detector and tracking results are integrated to get the target location. Experiments on a number of challenging video clips show that the proposed method outperforms some state-of-the-art tracking methods, especially for fast motion and drifts.
Recently, a class of tracking techniques called tracking by detection receive much attention in computer vision. These methods train a discriminative classsifier to separate the object from the background. The classifier bootstraps itself by using the current tracker state to extract positive and negative examples from the current frame. Slight inaccuracies in the tracker lead to incorrectly labeled training examples, which degrade the classifier and cause drift. In this paper, an effective algorithm is proposed to overcome the target drift. It takes the framework of tracking by detection. Median Flow (MF) is used as a tracker to improve the reliability of the tracking point; the detector is constituted with several weak classifiers of random ferns to cascade, and it is updated with online Multiple Instance Learning (MIL). Finally the detector and tracking results are integrated to get the target location. Experiments on a number of challenging video clips show that the proposed method outperforms some state-of-the-art tracking methods, especially for fast motion and drifts.
2014, 36(7): 1612-1618.
doi: 10.3724/SP.J.1146.2013.01144
Abstract:
Person re-identification, identifying the same persons images in an existing database come from non-overlapping camera views, is a valuable but challenging task. This paper proposes a statistical inference approach for person re-identification. A similarity measure of two person images is learned from a statistical inference perspective. Then the similarity measure is utilized to query a person from a gallery set. The proposed approach is demonstrated on VIPeR dataset, and the experiment shows that it outperforms the state-of-the-art approaches. Besides, it costs less time than the existing learning-based ones in training, and alleviates the over-fitting problem when there are few training data.
Person re-identification, identifying the same persons images in an existing database come from non-overlapping camera views, is a valuable but challenging task. This paper proposes a statistical inference approach for person re-identification. A similarity measure of two person images is learned from a statistical inference perspective. Then the similarity measure is utilized to query a person from a gallery set. The proposed approach is demonstrated on VIPeR dataset, and the experiment shows that it outperforms the state-of-the-art approaches. Besides, it costs less time than the existing learning-based ones in training, and alleviates the over-fitting problem when there are few training data.
2014, 36(7): 1619-1624.
doi: 10.3724/SP.J.1146.2013.01203
Abstract:
Few traditional road edge detection algorithms can be employed in rural road. An edge detection method based on vanishing point iteration revaluation is presented in this paper. Firstly, the texture orientation of pixel is estimated by Gabor filter, and the corresponding confidence is computed. Secondly, according to the texture orientation, the initial vanishing point is voted by pixels which their confidence are greater than threshold. Thirdly, with the initial vanishing point as starting point, a group of imaginary downward rays are founded, then the orientation consistency ratio weighted by both color difference and double-angle sine function is calculated, and the ray with maximum value is selected as the first road edge. Finally, the optimum vanishing point is given by sampling bilateral edges alternately, and thus two road edges are obtained. A variety of rural road pictures are tested by experiment, and some comparisons are made with the traditional algorithm. The results indicate the method is accurate and robust in rural road.
Few traditional road edge detection algorithms can be employed in rural road. An edge detection method based on vanishing point iteration revaluation is presented in this paper. Firstly, the texture orientation of pixel is estimated by Gabor filter, and the corresponding confidence is computed. Secondly, according to the texture orientation, the initial vanishing point is voted by pixels which their confidence are greater than threshold. Thirdly, with the initial vanishing point as starting point, a group of imaginary downward rays are founded, then the orientation consistency ratio weighted by both color difference and double-angle sine function is calculated, and the ray with maximum value is selected as the first road edge. Finally, the optimum vanishing point is given by sampling bilateral edges alternately, and thus two road edges are obtained. A variety of rural road pictures are tested by experiment, and some comparisons are made with the traditional algorithm. The results indicate the method is accurate and robust in rural road.
2014, 36(7): 1625-1630.
doi: 10.3724/SP.J.1146.2013.01089
Abstract:
In view of practical application of the target detection based on sensor networks, the remote target detection model is established. This paper addresses a novel Fusion Rule for Small-scale Sensor networks (FRSS) under the Neyman-Pearson criteria. The detection range or detection performance is improved by the way of data fusion. The fusion statistic (Counting statistic) is derived. Besides, the threshold of fusion center solving model is constructed through the randomized test and the closed-form expression of the detection performance is given. The performance of the target detection system under the ideal channel between local sensor nodes and fusion center and non-ideal channel using BPSK modulation is evaluated by numerical approach. Moreover, the Monte-Carlo approach is used to analyze comparatively the detection performance of FRSS rule and the previous Chair-Varshney rule, Bayes rule. The simulation results show that the proposed FRSS rule exhibits slight decline considering the detection performance compared with the other two rules. However, the FRSS rule requires less prior information and greatly reduces the amount of data transmission. The detection performance of FRSS is extremely improved compared with the single sensor node.
In view of practical application of the target detection based on sensor networks, the remote target detection model is established. This paper addresses a novel Fusion Rule for Small-scale Sensor networks (FRSS) under the Neyman-Pearson criteria. The detection range or detection performance is improved by the way of data fusion. The fusion statistic (Counting statistic) is derived. Besides, the threshold of fusion center solving model is constructed through the randomized test and the closed-form expression of the detection performance is given. The performance of the target detection system under the ideal channel between local sensor nodes and fusion center and non-ideal channel using BPSK modulation is evaluated by numerical approach. Moreover, the Monte-Carlo approach is used to analyze comparatively the detection performance of FRSS rule and the previous Chair-Varshney rule, Bayes rule. The simulation results show that the proposed FRSS rule exhibits slight decline considering the detection performance compared with the other two rules. However, the FRSS rule requires less prior information and greatly reduces the amount of data transmission. The detection performance of FRSS is extremely improved compared with the single sensor node.
2014, 36(7): 1631-1636.
doi: 10.3724/SP.J.1146.2013.01410
Abstract:
The prediction of airport noise plays an important role in airport noise control, flight schedule planning and surrounding designs of airport. However, the existing prediction models are complex and need so many highly accurate parameters that are monitored and collected as input of the model, hence adding difficulties to the prediction of airport noise. In order to solve these problems, this paper presents a prediction model based on the rough set and ensemble learning. Accordingly, the attributes of monitored noise data around airport is first reduced by the rough set and the subsets of attributes is produced then, the dynamic ensemble learning is used to combine base learners which are presented in three-dimensional coordinates based on the subsets of attributes. The results of experiments show that the proposed model can predict the noise of specific aircraft with full parameters being more accurately than existing models. And even if there is a lack in part of parameters, the prediction outcome of the model is able to approach the real value of airport noise while gradually increasing parameters.
The prediction of airport noise plays an important role in airport noise control, flight schedule planning and surrounding designs of airport. However, the existing prediction models are complex and need so many highly accurate parameters that are monitored and collected as input of the model, hence adding difficulties to the prediction of airport noise. In order to solve these problems, this paper presents a prediction model based on the rough set and ensemble learning. Accordingly, the attributes of monitored noise data around airport is first reduced by the rough set and the subsets of attributes is produced then, the dynamic ensemble learning is used to combine base learners which are presented in three-dimensional coordinates based on the subsets of attributes. The results of experiments show that the proposed model can predict the noise of specific aircraft with full parameters being more accurately than existing models. And even if there is a lack in part of parameters, the prediction outcome of the model is able to approach the real value of airport noise while gradually increasing parameters.
2014, 36(7): 1637-1641.
doi: 10.3724/SP.J.1146.2013.01365
Abstract:
This paper presents a new Direction-Of-Arrival (DOA) and power estimation algorithm based on two-stage weighted L1-norm penalty. In this scheme, this paper first obtains a better statistical performance vector measurement model by sum-average arithmetic using array covariance matrix elements. Then the sparse representation of the new model corresponding to the related overcomplete basis is successively constructed. This paper exploits MUSIC spectral function and initial estimation result as the weights to construct two-stage weighted L1-norm penalty reconstruction method. Consequently, this paper achieves the DOA and power estimation of multiple sources. Moreover, a reasonable regularization parameter is also selected by2 distribution function. The simulation results demonstrate that the proposed algorithm is able to provide higher resolution and estimation accuracy than the other state-of-the-art methods.
This paper presents a new Direction-Of-Arrival (DOA) and power estimation algorithm based on two-stage weighted L1-norm penalty. In this scheme, this paper first obtains a better statistical performance vector measurement model by sum-average arithmetic using array covariance matrix elements. Then the sparse representation of the new model corresponding to the related overcomplete basis is successively constructed. This paper exploits MUSIC spectral function and initial estimation result as the weights to construct two-stage weighted L1-norm penalty reconstruction method. Consequently, this paper achieves the DOA and power estimation of multiple sources. Moreover, a reasonable regularization parameter is also selected by2 distribution function. The simulation results demonstrate that the proposed algorithm is able to provide higher resolution and estimation accuracy than the other state-of-the-art methods.
2014, 36(7): 1642-1647.
doi: 10.3724/SP.J.1146.2013.01395
Abstract:
The definition of ideal access structure of XOR-based visual cryptography is given in this paper. The characteristics of ideal access structure are analyzed, and the construction algorithm of shares under ideal access structure is designed. Based on the above results, a new algorithm is proposed for dividing the general access structure into some ideal access structures, and the secret sharing and recovering algorithms are presented. Compared with the previous schemes, the proposed scheme realizes the perfect recovery of secret image, and the sizes of shares can be decreased efficiently.
The definition of ideal access structure of XOR-based visual cryptography is given in this paper. The characteristics of ideal access structure are analyzed, and the construction algorithm of shares under ideal access structure is designed. Based on the above results, a new algorithm is proposed for dividing the general access structure into some ideal access structures, and the secret sharing and recovering algorithms are presented. Compared with the previous schemes, the proposed scheme realizes the perfect recovery of secret image, and the sizes of shares can be decreased efficiently.
2014, 36(7): 1648-1655.
doi: 10.3724/SP.J.1146.2013.00750
Abstract:
As an important method of Side Channel Attacks (SCA), fault attacks offer the attacker plenty of possibilities to attack a cryptosystem, and nearly all the cryptographic algorithms are broken by using such kinds of attacks. So far many countermeasures against fault attacks are proposed. Howerever, most of them have drawbacks such as overhaed and fault coverage. In this paper, a circuit level countermeasure is proposed based on the strong robust of Null Convention Logic (NCL) circuits and dual-rail encode. The experimental evaluations show this countermeasure offers advantages on fault detecting capabilities and elimates fault propagation with lower cost, and it can be applied to kinds of automatization synthesis techniques.
As an important method of Side Channel Attacks (SCA), fault attacks offer the attacker plenty of possibilities to attack a cryptosystem, and nearly all the cryptographic algorithms are broken by using such kinds of attacks. So far many countermeasures against fault attacks are proposed. Howerever, most of them have drawbacks such as overhaed and fault coverage. In this paper, a circuit level countermeasure is proposed based on the strong robust of Null Convention Logic (NCL) circuits and dual-rail encode. The experimental evaluations show this countermeasure offers advantages on fault detecting capabilities and elimates fault propagation with lower cost, and it can be applied to kinds of automatization synthesis techniques.
2014, 36(7): 1656-1660.
doi: 10.3724/SP.J.1146.2013.01062
Abstract:
The Nonlinear Feedback Shift Register.(NFSR) is one of hot topics of stream cipher in recent studies. The uniqueness of a NFSR assuming to be decomposed into a cascade connection of smaller NFSRs is discussed in this paper. Firstly, the decomposition of Linear Feedback Shift Register.(LFSR) is equivalent to the decomposition of univariate polynomials over the finite field of two elements F2, thus it is unique. Secondly, for the case that a NFSR can be decomposed into a cascade connection of a NFSR into a LFSR, a necessary and sufficient condition is offered for a NFSR to have such a decomposition. Based on this condition, it is indicated that during all such decompositions, the largest LFSR is unique. However, the construction of counterexamples in a class shows that, for the general cases, the decomposition of a NFSR into a cascade connection of smaller NFSRs is not unique.
The Nonlinear Feedback Shift Register.(NFSR) is one of hot topics of stream cipher in recent studies. The uniqueness of a NFSR assuming to be decomposed into a cascade connection of smaller NFSRs is discussed in this paper. Firstly, the decomposition of Linear Feedback Shift Register.(LFSR) is equivalent to the decomposition of univariate polynomials over the finite field of two elements F2, thus it is unique. Secondly, for the case that a NFSR can be decomposed into a cascade connection of a NFSR into a LFSR, a necessary and sufficient condition is offered for a NFSR to have such a decomposition. Based on this condition, it is indicated that during all such decompositions, the largest LFSR is unique. However, the construction of counterexamples in a class shows that, for the general cases, the decomposition of a NFSR into a cascade connection of smaller NFSRs is not unique.
2014, 36(7): 1661-1666.
doi: 10.3724/SP.J.1146.2013.01717
Abstract:
SHACAL-2 algorithm is one of the standard block ciphers recommended by European NESSIE plan. It includes two kinds of nonlinear functions, the choice function and the major function. This paper studies mainly differential properties of the two nonlinear functions, and it is shown that the number of solutions of the differential equation is only related with the weight of the input difference when the difference only appears at the first position of the choice function, or only appears at the first or the second position of the major function. This observation is applied to the differential fault analysis on SHACAL-2. The results demonstrate that at least 160 random faults are needed to obtain 512 bit key with successful probability more than 60%, while at least 240 random faults are needed to obtain 512 bit key with successful probability more than 98%.
SHACAL-2 algorithm is one of the standard block ciphers recommended by European NESSIE plan. It includes two kinds of nonlinear functions, the choice function and the major function. This paper studies mainly differential properties of the two nonlinear functions, and it is shown that the number of solutions of the differential equation is only related with the weight of the input difference when the difference only appears at the first position of the choice function, or only appears at the first or the second position of the major function. This observation is applied to the differential fault analysis on SHACAL-2. The results demonstrate that at least 160 random faults are needed to obtain 512 bit key with successful probability more than 60%, while at least 240 random faults are needed to obtain 512 bit key with successful probability more than 98%.
2014, 36(7): 1667-1672.
doi: 10.3724/SP.J.1146.2013.00682
Abstract:
It is of great importance to guarantee the privacy of the database and users when the database is being queried. A private database queries protocol based on a quantum Third Party (TP) is proposed by utilizing the quantum correlation of three-photon Greenberger-Horne-Zeilinger (GHZ) states. The proposed protocol is highly tolerant of channel loss and robust against fake entangled state attack and quantum memory attack implemented by the third party. With the help of the TP, the amount of private information obtained by the users from the database is deterministically controllable in the proposed protocol. Furthermore, the true tripartite entanglement witness by using Mermin-Bell inequality can ensure the security of the protocol, which expands the application area of Device-Independent (DI) entanglement witnesses.
It is of great importance to guarantee the privacy of the database and users when the database is being queried. A private database queries protocol based on a quantum Third Party (TP) is proposed by utilizing the quantum correlation of three-photon Greenberger-Horne-Zeilinger (GHZ) states. The proposed protocol is highly tolerant of channel loss and robust against fake entangled state attack and quantum memory attack implemented by the third party. With the help of the TP, the amount of private information obtained by the users from the database is deterministically controllable in the proposed protocol. Furthermore, the true tripartite entanglement witness by using Mermin-Bell inequality can ensure the security of the protocol, which expands the application area of Device-Independent (DI) entanglement witnesses.
2014, 36(7): 1673-1679.
doi: 10.3724/SP.J.1146.2013.01291
Abstract:
This paper focuses on the energy-efficient power allocation in OFDMA systems. Different from the existing work, this paper proves that the optimal energy-efficient power allocation must have a special water-filling structure, named energy-efficient water-filling structure, by exploiting the strict pseudo-concavity of the energy efficiency function with respect to the power vector. Applying the energy-efficient water-filling structure, the original issue is simplified to a single-variable issue, and the closed-form optimal solution is further obtained. Based on the theoretical analysis, an optimal energy-efficient power allocation algorithm is proposed, where the optimal solution is achieved by sequentially searching within a finite number of water-level intervals. The simulation results demonstrate that the proposed algorithm achieves the optimal solution with significantly lower computational complexity compared with the conventional iterative methods.
This paper focuses on the energy-efficient power allocation in OFDMA systems. Different from the existing work, this paper proves that the optimal energy-efficient power allocation must have a special water-filling structure, named energy-efficient water-filling structure, by exploiting the strict pseudo-concavity of the energy efficiency function with respect to the power vector. Applying the energy-efficient water-filling structure, the original issue is simplified to a single-variable issue, and the closed-form optimal solution is further obtained. Based on the theoretical analysis, an optimal energy-efficient power allocation algorithm is proposed, where the optimal solution is achieved by sequentially searching within a finite number of water-level intervals. The simulation results demonstrate that the proposed algorithm achieves the optimal solution with significantly lower computational complexity compared with the conventional iterative methods.
2014, 36(7): 1680-1685.
doi: 10.3724/SP.J.1146.2013.01177
Abstract:
In cooperative spectrum sensing, previous numerical studies show that the sensing performance and the throughput of channel can be improved by increasing the secondary users which are participate in cooperative sensing. Due to the existence of channel capability, the throughput of channel can not be improved infinitely with the increasing number of secondary users, while the average throughput of secondary users decreases severely. In order to improve the average throughput of secondary users, the unimodal characteristics of the secondary users throughput are proved to be a function of the sensing time for any given fusion parameter in multi-channel environment. To solve this optimization issue, a cross iterative algorithm is proposed. Computer simulations show that when the average signal-to-noise ratio of secondary users is -10 dB, compared with the classical fusion rule, the proposed algorithm can gain more than 20% of the average throughput of secondary users.
In cooperative spectrum sensing, previous numerical studies show that the sensing performance and the throughput of channel can be improved by increasing the secondary users which are participate in cooperative sensing. Due to the existence of channel capability, the throughput of channel can not be improved infinitely with the increasing number of secondary users, while the average throughput of secondary users decreases severely. In order to improve the average throughput of secondary users, the unimodal characteristics of the secondary users throughput are proved to be a function of the sensing time for any given fusion parameter in multi-channel environment. To solve this optimization issue, a cross iterative algorithm is proposed. Computer simulations show that when the average signal-to-noise ratio of secondary users is -10 dB, compared with the classical fusion rule, the proposed algorithm can gain more than 20% of the average throughput of secondary users.
2014, 36(7): 1686-1692.
doi: 10.3724/SP.J.1146.2013.01241
Abstract:
In cognitive radio network, the underlay coexistence problem of the OFDMA based Secondary System (SS) with LTE-A systems is more and more important. This paper focuses on the resource allocation and interference mitigation issues in the aforementioned scenario. The dif?culty lies in the fact that even the subproblem, or power allocation with interference, is NP-Hard. Therefore, this paper proposes a two-phase Resource Allocation algorithm using maximum weighted Matching in the subcarrier allocation phase and interference Quantizing in the power allocation phase, referred to as the MQRA algorithm. As presented in this paper, the proposed MQRA algorithm has a good balance in performance and complexity, which ful?lls the stringent delay requirement of LTE-A systems.
In cognitive radio network, the underlay coexistence problem of the OFDMA based Secondary System (SS) with LTE-A systems is more and more important. This paper focuses on the resource allocation and interference mitigation issues in the aforementioned scenario. The dif?culty lies in the fact that even the subproblem, or power allocation with interference, is NP-Hard. Therefore, this paper proposes a two-phase Resource Allocation algorithm using maximum weighted Matching in the subcarrier allocation phase and interference Quantizing in the power allocation phase, referred to as the MQRA algorithm. As presented in this paper, the proposed MQRA algorithm has a good balance in performance and complexity, which ful?lls the stringent delay requirement of LTE-A systems.
2014, 36(7): 1693-1698.
doi: 10.3724/SP.J.1146.2013.01057
Abstract:
A spectrum sensing algorithm based on covariance matrix and array antenna is reported. It can perform blind spectrum sensing under a condition of uncertainty noise. The new test statistics for spectrum sensing based on the covariance matrix is constructed and the decision threshold based on the test statistics is derived, thus allowing the comparison of the test statistics with the decision threshold to make a final decision. In order to enable cognitive users to fully receive signals of cognitive primary user in the case that the arrival direction of primary signal and the receiving antenna of cognitive users is not consistent, this algorithm applies array antenna to the spectrum sensing based on covariance matrix. Simulation results show that the performance of the proposed spectrum sensing algorithm is superior to the Covariance Absolute Value Spectrum Sensing (CAVSS) algorithm proposed by Zeng (2009).
A spectrum sensing algorithm based on covariance matrix and array antenna is reported. It can perform blind spectrum sensing under a condition of uncertainty noise. The new test statistics for spectrum sensing based on the covariance matrix is constructed and the decision threshold based on the test statistics is derived, thus allowing the comparison of the test statistics with the decision threshold to make a final decision. In order to enable cognitive users to fully receive signals of cognitive primary user in the case that the arrival direction of primary signal and the receiving antenna of cognitive users is not consistent, this algorithm applies array antenna to the spectrum sensing based on covariance matrix. Simulation results show that the performance of the proposed spectrum sensing algorithm is superior to the Covariance Absolute Value Spectrum Sensing (CAVSS) algorithm proposed by Zeng (2009).
2014, 36(7): 1699-1705.
doi: 10.3724/SP.J.1146.2013.01148
Abstract:
High Efficiency Video Coding (HEVC) adopts a quadtree-based Coding Unit (CU) block partitioning structure which is flexible to adapt to various texture characteristics of images and can improve the coding efficiency significantly; however, it also introduces a great computation complexity. This paper proposes a fast CU splitting algorithm which can narrow CU depth range and early terminate the CU splitting. Firstly, in learning frame, based on the Sobel edge detection operator, this study obtains edge point threshold at each CU depth level to narrow the CU traversal depth range in the next several frames. Meanwhile, this paper introduces the statistical of Rate-Distortion (RD) cost of CU in the frame and calculates RD threshold of each depth level. Then, in the subsequent video frames, RD threshold is utilized to terminate early the CU splitting in the narrow depth range. The statistical parameters are periodically updated to cope with varying video content characteristics. The experimental results show that the proposed algorithm is able to save 59% encoding time on average with only 1.2% increasing on bit-rate which can observably improve the coding efficiency.
High Efficiency Video Coding (HEVC) adopts a quadtree-based Coding Unit (CU) block partitioning structure which is flexible to adapt to various texture characteristics of images and can improve the coding efficiency significantly; however, it also introduces a great computation complexity. This paper proposes a fast CU splitting algorithm which can narrow CU depth range and early terminate the CU splitting. Firstly, in learning frame, based on the Sobel edge detection operator, this study obtains edge point threshold at each CU depth level to narrow the CU traversal depth range in the next several frames. Meanwhile, this paper introduces the statistical of Rate-Distortion (RD) cost of CU in the frame and calculates RD threshold of each depth level. Then, in the subsequent video frames, RD threshold is utilized to terminate early the CU splitting in the narrow depth range. The statistical parameters are periodically updated to cope with varying video content characteristics. The experimental results show that the proposed algorithm is able to save 59% encoding time on average with only 1.2% increasing on bit-rate which can observably improve the coding efficiency.
2014, 36(7): 1706-1712.
doi: 10.3724/SP.J.1146.2013.01373
Abstract:
Most existing wireless network coding mechanisms do not consider the impact of wireless link quality on video transmission, resulting in the degradation in video quality. To address the above issue, this paper proposes an Optimized Opportunistic Network Coding (O2NC) mechanism, in combination with opportunistic routing, for video transmission in wireless networks. The candidate relay set is computed according to the transmission path gain and the importance of video data. Meanwhile, the comprehensive utility of a coded packet is estimated by considering the parameters of coding ratio and the priority of video data. On this basis, the coded packet with the largest utility is chosen for transmission. Simulation results demonstrate that, compared with typical network coding protocols, O2NC achieves significant performance improvement in terms of decodable frame ratio and average Peak Signal to Noise Ratio (PSNR) of video clips.
Most existing wireless network coding mechanisms do not consider the impact of wireless link quality on video transmission, resulting in the degradation in video quality. To address the above issue, this paper proposes an Optimized Opportunistic Network Coding (O2NC) mechanism, in combination with opportunistic routing, for video transmission in wireless networks. The candidate relay set is computed according to the transmission path gain and the importance of video data. Meanwhile, the comprehensive utility of a coded packet is estimated by considering the parameters of coding ratio and the priority of video data. On this basis, the coded packet with the largest utility is chosen for transmission. Simulation results demonstrate that, compared with typical network coding protocols, O2NC achieves significant performance improvement in terms of decodable frame ratio and average Peak Signal to Noise Ratio (PSNR) of video clips.
2014, 36(7): 1713-1719.
doi: 10.3724/SP.J.1146.2013.01151
Abstract:
Along with the growing expansion of network functions and continuous emerging of new protocols, the novel packet types and processing requirements are established in these protocols. The Software Defined Networking (SDN) makes the network innovation simpler based on the programmable flow table. However, it is still difficult for the SDN to support the arbitrary protocol processing. This paper takes into account the parsing and lookup procedure together, and proposes a hardware structure that could support elastic customization of the arbitrary protocols. By transforming the protocol processing procedure into a multi branched tree, users can arbitrarily define their own parsing and lookup processing, which is mapped into a hardware pipeline. The prototype on FPGA platform shows its flexibility in customizing protocols. The packet processing speed can achieve 390Gbps in hardware and the hardware resource utilization is significantly reduced compared to the existing scheme. The proposed architecture is quite meaningful for the data plane design of the SDN.
Along with the growing expansion of network functions and continuous emerging of new protocols, the novel packet types and processing requirements are established in these protocols. The Software Defined Networking (SDN) makes the network innovation simpler based on the programmable flow table. However, it is still difficult for the SDN to support the arbitrary protocol processing. This paper takes into account the parsing and lookup procedure together, and proposes a hardware structure that could support elastic customization of the arbitrary protocols. By transforming the protocol processing procedure into a multi branched tree, users can arbitrarily define their own parsing and lookup processing, which is mapped into a hardware pipeline. The prototype on FPGA platform shows its flexibility in customizing protocols. The packet processing speed can achieve 390Gbps in hardware and the hardware resource utilization is significantly reduced compared to the existing scheme. The proposed architecture is quite meaningful for the data plane design of the SDN.
2014, 36(7): 1720-1727.
doi: 10.3724/SP.J.1146.2013.01058
Abstract:
To deal with the issue that the interference increasing will make network capacity decrease and energy consumption increase in Wireless Sensor Network (WSN), the joint channel allocation and power control optimal game-theoretic model is established. To realize the links concurrent transmission, in the model the channel in which any link can keep itself successfully transmitting and does not influence the other links transmitting is regarded as the optional channel. Then based on the model a Joint Channel allocation and Power control optimal Game-theoretic algorithm for Concurrent transmission (JCPGC) is designed, in which the best respond is used to calculate the solution of the model, and the supermodular game theory is used to prove that JCPGC can get Nash Equilibrium (NE). Furthermore, the algorithm considers the independent and mutual influence relations between the channel allocation and the power control, hence it improves the network capacity. Simulation results show that JCPGC has higher network capacity, lower interference and energy consumption.
To deal with the issue that the interference increasing will make network capacity decrease and energy consumption increase in Wireless Sensor Network (WSN), the joint channel allocation and power control optimal game-theoretic model is established. To realize the links concurrent transmission, in the model the channel in which any link can keep itself successfully transmitting and does not influence the other links transmitting is regarded as the optional channel. Then based on the model a Joint Channel allocation and Power control optimal Game-theoretic algorithm for Concurrent transmission (JCPGC) is designed, in which the best respond is used to calculate the solution of the model, and the supermodular game theory is used to prove that JCPGC can get Nash Equilibrium (NE). Furthermore, the algorithm considers the independent and mutual influence relations between the channel allocation and the power control, hence it improves the network capacity. Simulation results show that JCPGC has higher network capacity, lower interference and energy consumption.
2014, 36(7): 1728-1734.
doi: 10.3724/SP.J.1146.2013.01066
Abstract:
Crucial node decision plays an important role during the network survivability study. Taking into account the node energy is limited, this study consider both the remaining life of the network and the added value of network energy consumption due to the node failure. A Critical Node Decision algorithm Based on Energy (CNDBE) is proposed, the problem which crucial node decision algorithm based on energy is solved. Simulation results show that, when the node which is decided by crucial node decision algorithm based on energy is protected, the network with CNDBE has a better survivability performance and has a longer lifetime when compared with Shortest Path Tree (SPT) and EnergyCritical Node Aware Spanning Tree for sensor networks (ENCAST).
Crucial node decision plays an important role during the network survivability study. Taking into account the node energy is limited, this study consider both the remaining life of the network and the added value of network energy consumption due to the node failure. A Critical Node Decision algorithm Based on Energy (CNDBE) is proposed, the problem which crucial node decision algorithm based on energy is solved. Simulation results show that, when the node which is decided by crucial node decision algorithm based on energy is protected, the network with CNDBE has a better survivability performance and has a longer lifetime when compared with Shortest Path Tree (SPT) and EnergyCritical Node Aware Spanning Tree for sensor networks (ENCAST).
2014, 36(7): 1735-1742.
doi: 10.3724/SP.J.1146.2013.01770
Abstract:
As for the interest flooding attack in Content-Centric Networking (CCN), this study proposes a new approach to mitigate interest flooding attack based on abnormal name prefix identification. This study utilizes the forwarding state in CCN routers to detect the interest flooding and identify abnormal name prefixes, and collaboratively defense the attack by sending the identified name prefixes to neighbors. Comparison between results of the proposed approach and others, the proposed approach is able to identify the abnormal name prefixes exactly, and quickly suppress malicious interest flooding without reducing the rate of normal interests.
As for the interest flooding attack in Content-Centric Networking (CCN), this study proposes a new approach to mitigate interest flooding attack based on abnormal name prefix identification. This study utilizes the forwarding state in CCN routers to detect the interest flooding and identify abnormal name prefixes, and collaboratively defense the attack by sending the identified name prefixes to neighbors. Comparison between results of the proposed approach and others, the proposed approach is able to identify the abnormal name prefixes exactly, and quickly suppress malicious interest flooding without reducing the rate of normal interests.
2014, 36(7): 1743-1748.
doi: 10.3724/SP.J.1146.2013.01079
Abstract:
Data aggregation is one of the most important approaches to alleviate the bottlenecks of resource in the Wireless Sensor Networks (WSNs). However, it is vulnerable to the attacks directing toward data confidentiality and integrity in an open and heterogeneous environment. To solve this problem, this paper proposes a Secure Data Aggregation (SDA) scheme based on the Homomorphic MAC for the WSNs, which is called SDA-HMAC. First, it adopts the Homomorphic MAC to check the aggregation data integrity; then it uses a homomorphic encryption scheme to ensure the data confidentiality; finally, it computes the hash function-based message authentication codes with time and key as the parameters to satisfy data freshness. The experimental simulation results and performance analyses denote that the SDA-HMAC can provide compared with other schemes, the data confidentiality, integrity, and freshness. It offers higher data transmission efficiency and more accurate data aggregation results while investing less volume of computation and communication.
Data aggregation is one of the most important approaches to alleviate the bottlenecks of resource in the Wireless Sensor Networks (WSNs). However, it is vulnerable to the attacks directing toward data confidentiality and integrity in an open and heterogeneous environment. To solve this problem, this paper proposes a Secure Data Aggregation (SDA) scheme based on the Homomorphic MAC for the WSNs, which is called SDA-HMAC. First, it adopts the Homomorphic MAC to check the aggregation data integrity; then it uses a homomorphic encryption scheme to ensure the data confidentiality; finally, it computes the hash function-based message authentication codes with time and key as the parameters to satisfy data freshness. The experimental simulation results and performance analyses denote that the SDA-HMAC can provide compared with other schemes, the data confidentiality, integrity, and freshness. It offers higher data transmission efficiency and more accurate data aggregation results while investing less volume of computation and communication.
2014, 36(7): 1755-1761.
doi: 10.3724/SP.J.1146.2013.01051
Abstract:
Many applications of Internet of Things (IoT) are performed by the continuous stream processing of the senor data and nodes replicas are required to guarantee system availability. However, the replicas backup and placement often bring the processing delay at run-time due to the consumption of resources such as memory and bandwidth. In this paper, a method is proposed as greedy fashion by the resources cost to place nodes replicas, which could tradeoff between the availability and overheads of the system. Moreover, in a practical system, the extensive experiments show that the availability of the proposed method can be provided in a more stable manner than the traditional random placement under the same conditions.
Many applications of Internet of Things (IoT) are performed by the continuous stream processing of the senor data and nodes replicas are required to guarantee system availability. However, the replicas backup and placement often bring the processing delay at run-time due to the consumption of resources such as memory and bandwidth. In this paper, a method is proposed as greedy fashion by the resources cost to place nodes replicas, which could tradeoff between the availability and overheads of the system. Moreover, in a practical system, the extensive experiments show that the availability of the proposed method can be provided in a more stable manner than the traditional random placement under the same conditions.
2014, 36(7): 1762-1766.
doi: 10.3724/SP.J.1146.2013.01427
Abstract:
The performance of optically controlled phased array antenna is greatly improved by the optical phase- shifting network with its advantages of broad bandwidth and high precision, however the additional phase noise of the optical phase-shifting network could lead to the deterioration of the space beam levels. Based on the analysis of the optical phase-shifting networks noise characteristics and phased array antenna theory, the formulas are derived in this paper, with a description of the relationship between the figure of Relative Intensity Noise (RIN) of laser, fiber links insertion loss, laser average power, and the main lobe level as well as the side lobe level. The simulation and theoretical study show that, with the typical parameter in the optical phase-shifting network, the increase of the three parameters is able to lead to reduce the main lobe gain and raise the side lobe level. The impact of RIN on lobe levels is more obvious. To optimize the lobe levels, the relative intensity noise of laser should be less than -140 dB/Hz.
The performance of optically controlled phased array antenna is greatly improved by the optical phase- shifting network with its advantages of broad bandwidth and high precision, however the additional phase noise of the optical phase-shifting network could lead to the deterioration of the space beam levels. Based on the analysis of the optical phase-shifting networks noise characteristics and phased array antenna theory, the formulas are derived in this paper, with a description of the relationship between the figure of Relative Intensity Noise (RIN) of laser, fiber links insertion loss, laser average power, and the main lobe level as well as the side lobe level. The simulation and theoretical study show that, with the typical parameter in the optical phase-shifting network, the increase of the three parameters is able to lead to reduce the main lobe gain and raise the side lobe level. The impact of RIN on lobe levels is more obvious. To optimize the lobe levels, the relative intensity noise of laser should be less than -140 dB/Hz.
2014, 36(7): 1767-1770.
doi: 10.3724/SP.J.1146.2013.01039
Abstract:
Microwave over-the-horizon radar can detect long distance and low altitude targets by means of the evaporation ducts over sea, however, the super refraction and multi-path propagation effects produce radar blind areas in evaporation duct where targets can not be detected. A method of antenna height optimization based on object function for microwave over-the-horizon radar is proposed in this paper. Radar detection performances are simulated in the three evaporation duct situations of stable stratification, neutral stratification and unstable stratification using numeric algorithm of radiowave propagation and radar performance evaluating models. The results of optimized antenna height is obtained for specific evaporation height and area weight functions. The method proposed can be used as a reference in microwave over-the-horizon radar design, detection performance analysis and self adaptive technology development in atmosphere environment.
Microwave over-the-horizon radar can detect long distance and low altitude targets by means of the evaporation ducts over sea, however, the super refraction and multi-path propagation effects produce radar blind areas in evaporation duct where targets can not be detected. A method of antenna height optimization based on object function for microwave over-the-horizon radar is proposed in this paper. Radar detection performances are simulated in the three evaporation duct situations of stable stratification, neutral stratification and unstable stratification using numeric algorithm of radiowave propagation and radar performance evaluating models. The results of optimized antenna height is obtained for specific evaporation height and area weight functions. The method proposed can be used as a reference in microwave over-the-horizon radar design, detection performance analysis and self adaptive technology development in atmosphere environment.
2014, 36(7): 1771-1774.
doi: 10.3724/SP.J.1146.2013.01256
Abstract:
In order to adapt to the requirement of the modern dual-band communication system, this paper presents a novel dual-band high gain antenna by adding an annular metal cylinder to the aperture in the center based on enhanced microwave transmission property of corrugated structure. Both the simulation and measurement results show that the gain of the proposed antenna is 12.0 dB and 12.9 dB at 12.7 GHz and 14.4 GHz separately, which is increased by 5.6 dB and 6.3 dB compared with the conventional antenna. Moreover, the Half Power Beam Width (HPBW) of the proposed antenna also gets much better.
In order to adapt to the requirement of the modern dual-band communication system, this paper presents a novel dual-band high gain antenna by adding an annular metal cylinder to the aperture in the center based on enhanced microwave transmission property of corrugated structure. Both the simulation and measurement results show that the gain of the proposed antenna is 12.0 dB and 12.9 dB at 12.7 GHz and 14.4 GHz separately, which is increased by 5.6 dB and 6.3 dB compared with the conventional antenna. Moreover, the Half Power Beam Width (HPBW) of the proposed antenna also gets much better.
2014, 36(7): 1775-1778.
doi: 10.3724/SP.J.1146.2013.01018
Abstract:
The current wireless Network Coding Relaying (NCR) is based on XOR operation or superposition operation, this paper proposes an Amplify-and-Forward NCR (AFNCR) cooperative scheme based on the multiplication operation. The relay node realizes the analog network coding by simply mutiplying the two received source signals, then amplifies and forwards it to the destinations. Compared with XOR-based NCR, the scheme is implemented by analog technology, thus the complexity of network coding at relay node is reduced greatly. Moreover, by mutiplying received signals with the local signals to realize the network decoding, its decoding algorithm is simpler than AFNCR. The theoretical analysis shows that its diversity gain is the same as the relay system without network coding. The simulation results show that the scheme gets the comparable performance with the existing NCR.
The current wireless Network Coding Relaying (NCR) is based on XOR operation or superposition operation, this paper proposes an Amplify-and-Forward NCR (AFNCR) cooperative scheme based on the multiplication operation. The relay node realizes the analog network coding by simply mutiplying the two received source signals, then amplifies and forwards it to the destinations. Compared with XOR-based NCR, the scheme is implemented by analog technology, thus the complexity of network coding at relay node is reduced greatly. Moreover, by mutiplying received signals with the local signals to realize the network decoding, its decoding algorithm is simpler than AFNCR. The theoretical analysis shows that its diversity gain is the same as the relay system without network coding. The simulation results show that the scheme gets the comparable performance with the existing NCR.
2014, 36(7): 1749-1754.
doi: 10.3724/SP.J.1146.2013.01154
Abstract:
Attribute signature attracts much attention due to the large-scale applications of cloud computing. Sensitive information in the document needs to be hidden in cloud computing environment, and Attribute Based Sanitizable Signature (ABSS) scheme in cloud computing environment is proposed to solve this issue. The ABSS scheme brings the character of sanitizable into Attribute Based Signature (ABS) in order to hide sensitive information, ensure signers anonymity and achieve fine-grained access control. The ABSS scheme constructed in this paper is proved to be unforged in the standard model. Analysis shows that the proposed ABSS scheme is more appropriate for cloud computing environment to hide the sensitive information of the data.
Attribute signature attracts much attention due to the large-scale applications of cloud computing. Sensitive information in the document needs to be hidden in cloud computing environment, and Attribute Based Sanitizable Signature (ABSS) scheme in cloud computing environment is proposed to solve this issue. The ABSS scheme brings the character of sanitizable into Attribute Based Signature (ABS) in order to hide sensitive information, ensure signers anonymity and achieve fine-grained access control. The ABSS scheme constructed in this paper is proved to be unforged in the standard model. Analysis shows that the proposed ABSS scheme is more appropriate for cloud computing environment to hide the sensitive information of the data.
