2010 Vol. 26 No. 10
2010, 26(10): 1441-1448.
Abstract：
Cooperative relay scheme has been proposed to deal with the heterogeneity of spectrum availability and traffic demand of secondary users in cognitive radio networks. According to this scheme, relay node can bridge the source and the destination using its common channels between those two nodes, as a result, spectrum resource can be better matched to traffic demand of secondary users and efficient spectrum allocation can be achieved. Two algorithms—parallel algorithm and greedy algorithm—are proposed based on maximum flow theory to solve the problem of relay selection and channel allocation in cognitive radio networks, in which the scheme of cooperative relay is used and common available channels probably exist. The complexity of both algorithms is analyzed. Simulation results show that both algorithms are able to allocate the resources more effectively, so as to improve the spectrum efficiency and the throughput of the network. Parallel algorithm can achieve the optimal solution, but its complexity grows rapidly with the channels’ common available degree. Limited by the parallel processing ability, it can only be applied when this degree is not high. Otherwise if the parallel processing ability is exceeded, the greedy algorithm should be selected, which may not necessarily be the optimal solution, but has low complexity and is closer to the optimum solution when there are more common channels.
Cooperative relay scheme has been proposed to deal with the heterogeneity of spectrum availability and traffic demand of secondary users in cognitive radio networks. According to this scheme, relay node can bridge the source and the destination using its common channels between those two nodes, as a result, spectrum resource can be better matched to traffic demand of secondary users and efficient spectrum allocation can be achieved. Two algorithms—parallel algorithm and greedy algorithm—are proposed based on maximum flow theory to solve the problem of relay selection and channel allocation in cognitive radio networks, in which the scheme of cooperative relay is used and common available channels probably exist. The complexity of both algorithms is analyzed. Simulation results show that both algorithms are able to allocate the resources more effectively, so as to improve the spectrum efficiency and the throughput of the network. Parallel algorithm can achieve the optimal solution, but its complexity grows rapidly with the channels’ common available degree. Limited by the parallel processing ability, it can only be applied when this degree is not high. Otherwise if the parallel processing ability is exceeded, the greedy algorithm should be selected, which may not necessarily be the optimal solution, but has low complexity and is closer to the optimum solution when there are more common channels.
2010, 26(10): 1449-1455.
Abstract：
Traditional HRRP (High Resolution Range Profile) reconstruction methods for SFR (Stepped-Frequency Radar) are sensitive to residual errors of motion compensation. However in this paper, several robust properties maintained by SFR echo after inter-pulse IFFT, which are insensitive to motion compensation errors, are proved firstly. Then base on these properties, a new HRRP reconstruction method is proposed, which not only eliminates the negative effect of Doppler cyclic shift of sub-HRRP on HRRP reconstruction, but also improves the accuracy of reconstruction effectively by pulse-envelop-weighting estimation. Analysis results using both simulated and field-measured data have verified the advantages of the proposed method.
Traditional HRRP (High Resolution Range Profile) reconstruction methods for SFR (Stepped-Frequency Radar) are sensitive to residual errors of motion compensation. However in this paper, several robust properties maintained by SFR echo after inter-pulse IFFT, which are insensitive to motion compensation errors, are proved firstly. Then base on these properties, a new HRRP reconstruction method is proposed, which not only eliminates the negative effect of Doppler cyclic shift of sub-HRRP on HRRP reconstruction, but also improves the accuracy of reconstruction effectively by pulse-envelop-weighting estimation. Analysis results using both simulated and field-measured data have verified the advantages of the proposed method.
2010, 26(10): 1456-1465.
Abstract：
As the most important expression of music’s motivation and subject, melody is specially studied in field of Music Information Retrieval (MIR), and researchers have made great efforts to find intelligent information processing and analysis methods for melody estimation and analysis. Based on the achievements in music cognition domain from both neuroscience and cognitive psychology, this paper applies the concept of auditory saliency (AS) and proposes a novel approach for melody detection in polyphonic music through the simulation of human’s musical cognition mechanism and characteristics. Firstly in the preprocessing stage, the constant Q transform (CQT) is applied for spectrum calculation, and spectrum model estimation. The AS feature for each semitone is calculated using Bayesian theory according to the semitone’s spectrum distribution over every frequency band. A special time accumulation artificial neural network is used to simulate the human neural system in order to detect salient features as melody candidate contents. In the post processing stage, a novel musicology and cognition related concept of Melody Stream is introduced to regulate melody candidates according to chord perception results. The results of the proposed melody detection methods and its similarity to human perception are evaluated on a small dataset with hundreds of music pieces that cover a number of typical music styles. Experiment results showed that the performance of the proposed strategy may cover more than 75% of the traditional melody line, and the subjective acceptance is measured to more than 90%.
As the most important expression of music’s motivation and subject, melody is specially studied in field of Music Information Retrieval (MIR), and researchers have made great efforts to find intelligent information processing and analysis methods for melody estimation and analysis. Based on the achievements in music cognition domain from both neuroscience and cognitive psychology, this paper applies the concept of auditory saliency (AS) and proposes a novel approach for melody detection in polyphonic music through the simulation of human’s musical cognition mechanism and characteristics. Firstly in the preprocessing stage, the constant Q transform (CQT) is applied for spectrum calculation, and spectrum model estimation. The AS feature for each semitone is calculated using Bayesian theory according to the semitone’s spectrum distribution over every frequency band. A special time accumulation artificial neural network is used to simulate the human neural system in order to detect salient features as melody candidate contents. In the post processing stage, a novel musicology and cognition related concept of Melody Stream is introduced to regulate melody candidates according to chord perception results. The results of the proposed melody detection methods and its similarity to human perception are evaluated on a small dataset with hundreds of music pieces that cover a number of typical music styles. Experiment results showed that the performance of the proposed strategy may cover more than 75% of the traditional melody line, and the subjective acceptance is measured to more than 90%.
2010, 26(10): 1466-1472.
Abstract：
In the application environment of using unmanned aerial vehicle (UAV) formations to locate the fixed target on the ground, which is radiant point, the angle between UAV and the fixed target, which transmit electronic signals, could be detected by using the Electronic Support Measurements (ESM) which carried on the UAVs, which compose the UAV formations, and the coordinate of the fixed target could be calculated by using the arrival of angle which is got by ESMs at each scan time. Suppose the sensors on the UAVs have identical measurement accuracy, and the measurement-error of the ESM is a zero mean Gaussian process noise. Under this condition, the accuracy of co-location would be affected by the formation of UAV formations. In this paper, we researched the relationships between the formation of UAV formations and the accuracy of co-location, which used the method of AOA. At first, we established the co-location model of two UAVs by using the geometry relationship of two UAVs, and derived an error model of co-location with UAV formations which based on the method of direction finding cross location. The second, Analyses the influence of positioning accuracy in different sensors' distance and different combination of azimuth angles by using the error model of co-location which derived at the first stage, Based on the analysis above, We got the conclusions about the relationship between the formation of UAV formations and the accuracy of co-location. Finally, we propose a function of data fusion selection for measurement data based on the method of bearing-only location and use the function to improve the method of AOA location. The validity of the improved method is verified by the results of simulation. At the same time, the conclusions, proposed in this paper, which described the relationships between the formation of UAV formations and the accuracy of co-location could be used in optimal UAV formations path planning.
In the application environment of using unmanned aerial vehicle (UAV) formations to locate the fixed target on the ground, which is radiant point, the angle between UAV and the fixed target, which transmit electronic signals, could be detected by using the Electronic Support Measurements (ESM) which carried on the UAVs, which compose the UAV formations, and the coordinate of the fixed target could be calculated by using the arrival of angle which is got by ESMs at each scan time. Suppose the sensors on the UAVs have identical measurement accuracy, and the measurement-error of the ESM is a zero mean Gaussian process noise. Under this condition, the accuracy of co-location would be affected by the formation of UAV formations. In this paper, we researched the relationships between the formation of UAV formations and the accuracy of co-location, which used the method of AOA. At first, we established the co-location model of two UAVs by using the geometry relationship of two UAVs, and derived an error model of co-location with UAV formations which based on the method of direction finding cross location. The second, Analyses the influence of positioning accuracy in different sensors' distance and different combination of azimuth angles by using the error model of co-location which derived at the first stage, Based on the analysis above, We got the conclusions about the relationship between the formation of UAV formations and the accuracy of co-location. Finally, we propose a function of data fusion selection for measurement data based on the method of bearing-only location and use the function to improve the method of AOA location. The validity of the improved method is verified by the results of simulation. At the same time, the conclusions, proposed in this paper, which described the relationships between the formation of UAV formations and the accuracy of co-location could be used in optimal UAV formations path planning.
2010, 26(10): 1473-1477.
Abstract：
The complicated operation of finding direction must be reduced to satisfy the real time finding direction processing. Now, there are many finding direction algorithms. The MUSIC like algorithm based on the uniform circle array is applied to the practice system. Because this algorithm has width frequency ranges. Both of the elevation and azimuth can be estimated. This algorithm also can provide accurate estimation efficiently. The performance of this algorithm is solidity and robust. The direction of arrival estimation has the same capability from the different azimuth. Analysis is done on the steering vector of the uniform circular array aiming at the geometry of the uniform circular array. Then, a fast DOA estimation method based on cosine characteristic is put forward. First, this method constructs the statistical variable. This variable has relation with elevation only, which has no relation with azimuth. So the estimation of elevation angle can be get by cosine characteristic. Then, the two dimensional search is replaced by the one dimensional search by the estimation of elevation angle. The complicated operation of finding direction is reduced consumedly. This algorithm can provide accurate estimation efficiently. This algorithm is suited to applied situation of the many array number. Compared with the existing 2-D direction of arrival estimation algorithm, the superiority of this algorithm is evident in the computational load. At the same time, there are two signals in the practice narrowband system. The two signals interacts each other. This paper distills the anticipant signal by digital filter to reduce the effect on small signal. The simulation results validate the efficiency of the method. Performance of this algorithm is robust than the other algorithms. Compared with the existing finding direction algorithm, the superiority of this algorithm is evident in the computational load.
The complicated operation of finding direction must be reduced to satisfy the real time finding direction processing. Now, there are many finding direction algorithms. The MUSIC like algorithm based on the uniform circle array is applied to the practice system. Because this algorithm has width frequency ranges. Both of the elevation and azimuth can be estimated. This algorithm also can provide accurate estimation efficiently. The performance of this algorithm is solidity and robust. The direction of arrival estimation has the same capability from the different azimuth. Analysis is done on the steering vector of the uniform circular array aiming at the geometry of the uniform circular array. Then, a fast DOA estimation method based on cosine characteristic is put forward. First, this method constructs the statistical variable. This variable has relation with elevation only, which has no relation with azimuth. So the estimation of elevation angle can be get by cosine characteristic. Then, the two dimensional search is replaced by the one dimensional search by the estimation of elevation angle. The complicated operation of finding direction is reduced consumedly. This algorithm can provide accurate estimation efficiently. This algorithm is suited to applied situation of the many array number. Compared with the existing 2-D direction of arrival estimation algorithm, the superiority of this algorithm is evident in the computational load. At the same time, there are two signals in the practice narrowband system. The two signals interacts each other. This paper distills the anticipant signal by digital filter to reduce the effect on small signal. The simulation results validate the efficiency of the method. Performance of this algorithm is robust than the other algorithms. Compared with the existing finding direction algorithm, the superiority of this algorithm is evident in the computational load.
2010, 26(10): 1478-1483.
Abstract：
Beamforming is one of the key techniques for the multiple-input multiple-output (MIMO) wireless communication systems, which enables the system to achieve higher transmission reliability when the full instantaneous channel state information(CSI) of all the online users are available. This makes the crowded spectrum resources become more limited. In this paper, since the Discrete Fourier Transform (DFT) based codebook is simple to generate, it is employed to quantize CSI so that the quantity of channel feedback of the system is reduced in the downlink of Long Term Evolution (LTE) with MIMO. Moreover, a novel beamforming scheme adopting the DFT-based codebook is also proposed, which dramatically reduces the quantity of feedback. The proposed beamforming scheme is based on the channel quality-to-interference ratio (QIR) quantizing criteria, which is defined in the paper. The QIR quantizing criteria jointly considers the influences of the quality of quantized channels and the mutual interference among the subchannels. Hence, the proposed scheme outperforms the traditional quantizing criteria, where only one factor is concerned. The extensive simulation results verify that the novel beamforming scheme can reduce the quantity of feedback greatly. Besides, its throughput is better than that of the random beamforming (RBF) with a little feedback (that is, the logarithm of the codebook size). The simulations also show that, under the low SNR scenario, the performance of the proposed scheme, with rather small feedback, is even better than that of the eigen-beamforming (EBF). Thus, the novel beamforming scheme proves to be effective.
Beamforming is one of the key techniques for the multiple-input multiple-output (MIMO) wireless communication systems, which enables the system to achieve higher transmission reliability when the full instantaneous channel state information(CSI) of all the online users are available. This makes the crowded spectrum resources become more limited. In this paper, since the Discrete Fourier Transform (DFT) based codebook is simple to generate, it is employed to quantize CSI so that the quantity of channel feedback of the system is reduced in the downlink of Long Term Evolution (LTE) with MIMO. Moreover, a novel beamforming scheme adopting the DFT-based codebook is also proposed, which dramatically reduces the quantity of feedback. The proposed beamforming scheme is based on the channel quality-to-interference ratio (QIR) quantizing criteria, which is defined in the paper. The QIR quantizing criteria jointly considers the influences of the quality of quantized channels and the mutual interference among the subchannels. Hence, the proposed scheme outperforms the traditional quantizing criteria, where only one factor is concerned. The extensive simulation results verify that the novel beamforming scheme can reduce the quantity of feedback greatly. Besides, its throughput is better than that of the random beamforming (RBF) with a little feedback (that is, the logarithm of the codebook size). The simulations also show that, under the low SNR scenario, the performance of the proposed scheme, with rather small feedback, is even better than that of the eigen-beamforming (EBF). Thus, the novel beamforming scheme proves to be effective.
2010, 26(10): 1484-1488.
Abstract：
Aiming at the detection problem of dim target in infrared image that contains background interference and noise, a detection method is proposed based on lifting wavelet transform and recursive minimum within-cluster absolute difference. Firstly, the image is preprocessed. The original image is denoised based on lifting wavelet transform, then the background of denoised image is suppressed by Top-hat operator. At the same time, the background of original image is suppressed by Top-hat operator, then Top-hat operator is further used after the residual image is denoised. Addition of the above-mentioned two resultant images gives the preprocessed image. Secondly, the preprocessed image is segmented using the threshold selected by recursive minimum within-cluster absolute difference. Lots of experiments are done with infrared images including small targets, and a comparison is made with the detection methods for infrared small target based on morphological filter and based on wavelet and morphology. The results show that the signal-to-noise ratio of the suggested method is improved, and detection rate increases by 15% and 10%, respectively.
Aiming at the detection problem of dim target in infrared image that contains background interference and noise, a detection method is proposed based on lifting wavelet transform and recursive minimum within-cluster absolute difference. Firstly, the image is preprocessed. The original image is denoised based on lifting wavelet transform, then the background of denoised image is suppressed by Top-hat operator. At the same time, the background of original image is suppressed by Top-hat operator, then Top-hat operator is further used after the residual image is denoised. Addition of the above-mentioned two resultant images gives the preprocessed image. Secondly, the preprocessed image is segmented using the threshold selected by recursive minimum within-cluster absolute difference. Lots of experiments are done with infrared images including small targets, and a comparison is made with the detection methods for infrared small target based on morphological filter and based on wavelet and morphology. The results show that the signal-to-noise ratio of the suggested method is improved, and detection rate increases by 15% and 10%, respectively.
2010, 26(10): 1489-1494.
Abstract：
The problem of sensor set selection for cooperative spectrum sensing in cognitive radio networks is considered in this paper. To the best of our knowledge, this is the first effort to select sensor set for cooperative spectrum sensing in cognitive radio. Under spatial correlation channels, the cooperative gain of the newly added cooperative sensor decreases and converges to zero as the number of cooperative sensors increases. Meanwhile, the system resources usage efficiency decreases as the number of cooperative sensors increases, since the consumption of system resources, such as the total transmission power of the signal measurements and the amount of overhead traffic in the cognitive radio network, grows approximately linearly with the number of cooperative sensors. Therefore, the number of cooperative sensors to use is a compromise between sensing performance and system resources usage efficiency. A greedy based cooperative sensor set selecting algorithm is proposed which can use a threshold acquired by compromising between sensing performance and resources usage efficiency to select a cooperative sensor set. Numerical results illustrate the effectiveness and reliability of the proposed sensor set selecting algorithm.
The problem of sensor set selection for cooperative spectrum sensing in cognitive radio networks is considered in this paper. To the best of our knowledge, this is the first effort to select sensor set for cooperative spectrum sensing in cognitive radio. Under spatial correlation channels, the cooperative gain of the newly added cooperative sensor decreases and converges to zero as the number of cooperative sensors increases. Meanwhile, the system resources usage efficiency decreases as the number of cooperative sensors increases, since the consumption of system resources, such as the total transmission power of the signal measurements and the amount of overhead traffic in the cognitive radio network, grows approximately linearly with the number of cooperative sensors. Therefore, the number of cooperative sensors to use is a compromise between sensing performance and system resources usage efficiency. A greedy based cooperative sensor set selecting algorithm is proposed which can use a threshold acquired by compromising between sensing performance and resources usage efficiency to select a cooperative sensor set. Numerical results illustrate the effectiveness and reliability of the proposed sensor set selecting algorithm.
2010, 26(10): 1495-1499.
Abstract：
Recently, in the fields of machine learning, how to use support vector machine for multi-class objects classification while improving the classification efficiency of the classifier has become one of the main study points, effective solutions to this problem have great significance for improving the probability of target recognition. In this paper we present a GA-based SVM decision tree algorithm. In our algorithm, we randomly generate a decision tree to build the SVM classifier on the same test samples of the classification accuracy rate as the genetic algorithm fitness function, then with the help of genetic algorithm,we can find the optimal decision tree, and then construct an optimal decision tree SVM classifier as the optimal SVM classifier. We use this algorithm to deal with the low altitude flying passive acoustic target identify problem. Experiment results show that the proposed method is more precise and less testing time cost than the traditional 1-a-1,1-a-r,SVM-DL,GADTSVM methods.
Recently, in the fields of machine learning, how to use support vector machine for multi-class objects classification while improving the classification efficiency of the classifier has become one of the main study points, effective solutions to this problem have great significance for improving the probability of target recognition. In this paper we present a GA-based SVM decision tree algorithm. In our algorithm, we randomly generate a decision tree to build the SVM classifier on the same test samples of the classification accuracy rate as the genetic algorithm fitness function, then with the help of genetic algorithm,we can find the optimal decision tree, and then construct an optimal decision tree SVM classifier as the optimal SVM classifier. We use this algorithm to deal with the low altitude flying passive acoustic target identify problem. Experiment results show that the proposed method is more precise and less testing time cost than the traditional 1-a-1,1-a-r,SVM-DL,GADTSVM methods.
2010, 26(10): 1500-1503.
Abstract：
Inverse scaled Fourier transformation (ISFT) algorithm uses the inverse scaling property of ISFT to perform the range cell migration correction (RCMC) of SAR echoes in two-dimensional frequency domain in order to improve the corrected precision of RCMC and the computational efficiency, so it has become an important frequency domain algorithm. The paper studied the processing procedure of the algorithm, and redefined the expression of the chirp rate used to the range compression, which made the algorithm to accommodate secondary range compression (SRC). Further, one-order term coefficient of the range frequency in ISFT algorithm was modified. The modified ISFT algorithm is suited for the demands on data processing of squint mode SAR. The simulation tests validated the modified ISFT algorithm to process the squint mode SAR data.
Inverse scaled Fourier transformation (ISFT) algorithm uses the inverse scaling property of ISFT to perform the range cell migration correction (RCMC) of SAR echoes in two-dimensional frequency domain in order to improve the corrected precision of RCMC and the computational efficiency, so it has become an important frequency domain algorithm. The paper studied the processing procedure of the algorithm, and redefined the expression of the chirp rate used to the range compression, which made the algorithm to accommodate secondary range compression (SRC). Further, one-order term coefficient of the range frequency in ISFT algorithm was modified. The modified ISFT algorithm is suited for the demands on data processing of squint mode SAR. The simulation tests validated the modified ISFT algorithm to process the squint mode SAR data.
2010, 26(10): 1504-1509.
Abstract：
This paper investigates some limited feedback approaches based on clustering in MIMO-OFDM beamforming systems with limited feedback. Exploiting the channel frequency correlation across adjacent subcarriers within a cluster, a low complexity channel mean clustering is proposed. In the approach, the optimal cluster beamforming vector is selected in a pre-designed codebook with mean channel response. Additionally, exploiting the residual frequency correlation between the cluster beamforming vectors, both recursive feedback and trellis-based feedback are proposed to reduce feedback rate. In the proposed approaches, the new codebook of current cluster consists of the codewords within in the neighborhood of previous cluster codeword, hence reducing the number of feedback bits remarkably. The simulation results show that, the channel mean clustering can obtain good BER performance with low computational complexity, and the feedback reduction approaches can further reduce feedback rate compared to traditional clustering methods. The recursive feedback approach has a little performance loss while the performance loss of the trellis-based feedback approach can be ignored.
This paper investigates some limited feedback approaches based on clustering in MIMO-OFDM beamforming systems with limited feedback. Exploiting the channel frequency correlation across adjacent subcarriers within a cluster, a low complexity channel mean clustering is proposed. In the approach, the optimal cluster beamforming vector is selected in a pre-designed codebook with mean channel response. Additionally, exploiting the residual frequency correlation between the cluster beamforming vectors, both recursive feedback and trellis-based feedback are proposed to reduce feedback rate. In the proposed approaches, the new codebook of current cluster consists of the codewords within in the neighborhood of previous cluster codeword, hence reducing the number of feedback bits remarkably. The simulation results show that, the channel mean clustering can obtain good BER performance with low computational complexity, and the feedback reduction approaches can further reduce feedback rate compared to traditional clustering methods. The recursive feedback approach has a little performance loss while the performance loss of the trellis-based feedback approach can be ignored.
2010, 26(10): 1510-1515.
Abstract：
A lot of ambient noises are non-Gaussian in actual blind multi-user detection systems, and non-Gaussianity often results in significant performance degradation or even invalidation to constant modulus blind multi-user detection algorithm with the channel model premised upon the Gaussian noise assumption. Alpha-stable distributions are one of the most important non-Gaussian models and can provide useful model for many phenomena observed in different fields. Facing with this problem, we present a fractional lower order statistics based generalized constant modulus algorithm (FLOS-GCMA). This FLOS-GCMA, which is a generalization of FLOS-CMA, can work efficiently under non-Gaussian noise condition and can be used in many areas. With DS-CDMA system as an example, we compare our algorithm with the constant modulus algorithm (CMA) and fractional lower order statistics based constant modulus algorithm (FLOS-CMA) analytically and numerically. The simulation results show that FLOS-GCMA can suppress multiple access interference (MAI) and non-Gaussian noise effectively, and converges fast either under Gaussian noise or alpha-stable distributed noise environment.
A lot of ambient noises are non-Gaussian in actual blind multi-user detection systems, and non-Gaussianity often results in significant performance degradation or even invalidation to constant modulus blind multi-user detection algorithm with the channel model premised upon the Gaussian noise assumption. Alpha-stable distributions are one of the most important non-Gaussian models and can provide useful model for many phenomena observed in different fields. Facing with this problem, we present a fractional lower order statistics based generalized constant modulus algorithm (FLOS-GCMA). This FLOS-GCMA, which is a generalization of FLOS-CMA, can work efficiently under non-Gaussian noise condition and can be used in many areas. With DS-CDMA system as an example, we compare our algorithm with the constant modulus algorithm (CMA) and fractional lower order statistics based constant modulus algorithm (FLOS-CMA) analytically and numerically. The simulation results show that FLOS-GCMA can suppress multiple access interference (MAI) and non-Gaussian noise effectively, and converges fast either under Gaussian noise or alpha-stable distributed noise environment.
2010, 26(10): 1516-1520.
Abstract：
The traditional methods for the direction-of-arrival (DOA) estimation of coherently distributed (CD) sources generally need perform a grid searching or the eigendecomposition of the high-dimensional sample covariance matrix, and the computational complexities of them are obviously higher. Aiming at the problem mentioned above, this paper proposes a low-complexity estimation method for the central DOA of CD sources by using uniform linear array (ULA). The proposed method estimates the central DOAs of distributed sources by combining the rotational invariance property of shifted array with propagator method. The method need not any peak-finding searching and the eigendecomposition of the sample covariance matrix, thus it provides a lower computational complexity compared to the classical subspace methods. The method has good estimation performance under small angular spread condition and its performance approaches greatly distributed signal parameter estimator (DSPE) algorithm. And it is also a blind estimator, which does not depend practically on the specific angular distribution shapes of distributed sources. Simulation results show that the proposed method is effective.
The traditional methods for the direction-of-arrival (DOA) estimation of coherently distributed (CD) sources generally need perform a grid searching or the eigendecomposition of the high-dimensional sample covariance matrix, and the computational complexities of them are obviously higher. Aiming at the problem mentioned above, this paper proposes a low-complexity estimation method for the central DOA of CD sources by using uniform linear array (ULA). The proposed method estimates the central DOAs of distributed sources by combining the rotational invariance property of shifted array with propagator method. The method need not any peak-finding searching and the eigendecomposition of the sample covariance matrix, thus it provides a lower computational complexity compared to the classical subspace methods. The method has good estimation performance under small angular spread condition and its performance approaches greatly distributed signal parameter estimator (DSPE) algorithm. And it is also a blind estimator, which does not depend practically on the specific angular distribution shapes of distributed sources. Simulation results show that the proposed method is effective.
2010, 26(10): 1521-1525.
Abstract：
High altitude platform communications systems possess the advantages of both terrestrial wireless communications system and satellite communications system, and will play an important role in future communications infrastructure. In this paper, geographical information based call admission control (CAC) schemes are discussed. Call density restricted CAC (DR-CAC) scheme and handover time interval restricted CAC (TR-CAC) scheme are analyzed. We present a handover Performance Restricted CAC (PR-CAC) scheme, in which the handover dropping probability introduced by a new call arrival is calculated using the geographical information, and a handover performance threshold is set to restrict the handover performance and to improve the call blocking performance. Simulation results show that the call blocking probability for the modified TR-CAC scheme is 13.6% lower than that for the original scheme with a fixed threshold of handover dropping probability. In the application of the TR-CAC scheme, the handover interval time threshold can be adapted according to the current traffic to minimize the call blocking probability while meeting the handover dropping performance. The PR-CAC scheme can keep the handover dropping performance to a specific threshold. Moreover, the PR-CAC scheme can achieve better call blocking performance than the other schemes mentioned in this paper, with an improvement of 25.3% compared with time based channel reservation algorithm, and with an improvement of 6.5% compared with TR-CAC.
High altitude platform communications systems possess the advantages of both terrestrial wireless communications system and satellite communications system, and will play an important role in future communications infrastructure. In this paper, geographical information based call admission control (CAC) schemes are discussed. Call density restricted CAC (DR-CAC) scheme and handover time interval restricted CAC (TR-CAC) scheme are analyzed. We present a handover Performance Restricted CAC (PR-CAC) scheme, in which the handover dropping probability introduced by a new call arrival is calculated using the geographical information, and a handover performance threshold is set to restrict the handover performance and to improve the call blocking performance. Simulation results show that the call blocking probability for the modified TR-CAC scheme is 13.6% lower than that for the original scheme with a fixed threshold of handover dropping probability. In the application of the TR-CAC scheme, the handover interval time threshold can be adapted according to the current traffic to minimize the call blocking probability while meeting the handover dropping performance. The PR-CAC scheme can keep the handover dropping performance to a specific threshold. Moreover, the PR-CAC scheme can achieve better call blocking performance than the other schemes mentioned in this paper, with an improvement of 25.3% compared with time based channel reservation algorithm, and with an improvement of 6.5% compared with TR-CAC.
2010, 26(10): 1526-1531.
Abstract：
The performance analysis of multiple tracks association is one of the key and difficult issues in the space-based optical passive angle tracking system. For the typical nearest nerghbor track association algorithm, this paper proposes a novel performance analysis method of passive multisensor multitarget track association based on multiple Bernoulli model. Firstly, the probability distribution of the association hinge angle difference statistic is modeled exactly. Secondly, the equivalent condition of the nearest neighbor track association algorithm in multiple targets situation is analyzed; the correct association probability of each target in multiple targets sitation is calculated. Finally, each correct association probability is treated as the succesful rate of a Bernoulli trial, and then the problem of the holistic association performance about all targets is modeled as the multiple Bernoulli process. On this basis, the association performance in multiple targets situation is derived theoreticly. A Monte Carlo simulation in dense targets scenario is used to analyze the performance analysis method, the efficiency of this performance analysis method is verified by the simulation results. It seems that some analysis results can provide references to engineering applications, such as multiple sensors management.
The performance analysis of multiple tracks association is one of the key and difficult issues in the space-based optical passive angle tracking system. For the typical nearest nerghbor track association algorithm, this paper proposes a novel performance analysis method of passive multisensor multitarget track association based on multiple Bernoulli model. Firstly, the probability distribution of the association hinge angle difference statistic is modeled exactly. Secondly, the equivalent condition of the nearest neighbor track association algorithm in multiple targets situation is analyzed; the correct association probability of each target in multiple targets sitation is calculated. Finally, each correct association probability is treated as the succesful rate of a Bernoulli trial, and then the problem of the holistic association performance about all targets is modeled as the multiple Bernoulli process. On this basis, the association performance in multiple targets situation is derived theoreticly. A Monte Carlo simulation in dense targets scenario is used to analyze the performance analysis method, the efficiency of this performance analysis method is verified by the simulation results. It seems that some analysis results can provide references to engineering applications, such as multiple sensors management.
2010, 26(10): 1532-1538.
Abstract：
A de-noising method based on independent component analysis and wavelet transformation is proposed in this paper to remove ECG interference. Firstly, the independent components of ECG are gotten by employing ICA to EMGdi signals. Select a suitable high-pass filter to remove the ECG components, and the approximate weight of other EMGdi components are removed after wavelet decomposition at the fifth scale, on the other hand, the details are reconstructed. Finally, reflect these processed independent components back to the original signal space. Experiment on collected 5 channel clinical EMGdi signal is presented. Comparing the results with the traditional ICA method, it shows that the method proposed is better than the traditional ICA method in removing ECG interference.
A de-noising method based on independent component analysis and wavelet transformation is proposed in this paper to remove ECG interference. Firstly, the independent components of ECG are gotten by employing ICA to EMGdi signals. Select a suitable high-pass filter to remove the ECG components, and the approximate weight of other EMGdi components are removed after wavelet decomposition at the fifth scale, on the other hand, the details are reconstructed. Finally, reflect these processed independent components back to the original signal space. Experiment on collected 5 channel clinical EMGdi signal is presented. Comparing the results with the traditional ICA method, it shows that the method proposed is better than the traditional ICA method in removing ECG interference.
2010, 26(10): 1539-1543.
Abstract：
To solve the problem that we can’t take the right interference suppression method to improve the performance of direct sequence spread spectrum(DSSS) communication system because of the unknown interference types, an algorithm to automatically recognize interferences is proposed. First, the mathematical models of 8 important interferences in DSSS communication system are made; Then, the features of interferences from time domain, frequency domain and time-frequency domain are extracted; And finally, a fifth-order automatic interference recognizer based on decision tree support vector machine is constructed, and the automatic recognition of the interferences is realized. Simulation results demonstrate that the proposed algorithm provides a very high recognition rate when ISR isn’t lower than 9dB.
To solve the problem that we can’t take the right interference suppression method to improve the performance of direct sequence spread spectrum(DSSS) communication system because of the unknown interference types, an algorithm to automatically recognize interferences is proposed. First, the mathematical models of 8 important interferences in DSSS communication system are made; Then, the features of interferences from time domain, frequency domain and time-frequency domain are extracted; And finally, a fifth-order automatic interference recognizer based on decision tree support vector machine is constructed, and the automatic recognition of the interferences is realized. Simulation results demonstrate that the proposed algorithm provides a very high recognition rate when ISR isn’t lower than 9dB.
2010, 26(10): 1544-1551.
Abstract：
Speech information hiding has long been a hot point and also a problem in domain of information security. In this paper, a new speech information hiding model based on theories of masking effect and spread spectrum codes is introduced, which is highly transparent using hopping fractional fourier transform. Introduction of this model is started with two algorithms derived from frequency masking—a confidential information embedding algorithm in frational fourier transform domain and an extracting algorithm in frational correlation cepstrum domain. Another wide interval multi-system pseudo-random sequence is also put forward in order to control the fractional order factors. According to the theoretical analysis and experimental result, this model is highly transparent that confidential information can not be found in time domain, frequency domain or even cepstrum domain. also, this model performs well in anti-noise. Our study suggests that this model has high value and good prospect in application.
Speech information hiding has long been a hot point and also a problem in domain of information security. In this paper, a new speech information hiding model based on theories of masking effect and spread spectrum codes is introduced, which is highly transparent using hopping fractional fourier transform. Introduction of this model is started with two algorithms derived from frequency masking—a confidential information embedding algorithm in frational fourier transform domain and an extracting algorithm in frational correlation cepstrum domain. Another wide interval multi-system pseudo-random sequence is also put forward in order to control the fractional order factors. According to the theoretical analysis and experimental result, this model is highly transparent that confidential information can not be found in time domain, frequency domain or even cepstrum domain. also, this model performs well in anti-noise. Our study suggests that this model has high value and good prospect in application.
2010, 26(10): 1552-1559.
Abstract：
Radar detection and tracking of the low signal-noise-ratio aircraft wake vortices have become an important direction in aviation safety and airport capacity. Usually low-threshold detection can improve the detection performance of the weak wake vortices, but large false alarm rate may cause the tracker to be disabled. Based on the linear spatial distribution model, the wake vortices tracking algorithm was put proposed to estimate the wake track. First, the whole wake is regarded as a linear target of joint motion, the function between measurement likelihood and wake states such as center, slope angle, and length is got, and it is helpful to carry out data association when the wake measurement number changed and in dense multi-return environments. Then, the states of the whole wake were estimated using particle filtering. Simulation results show that the proposed algorithm can accurately estimates the real wake states in the condition of low-threshold detection. This research is helpful to the wake return identification using the wake vortex characteristics in airport application and early warning system.
Radar detection and tracking of the low signal-noise-ratio aircraft wake vortices have become an important direction in aviation safety and airport capacity. Usually low-threshold detection can improve the detection performance of the weak wake vortices, but large false alarm rate may cause the tracker to be disabled. Based on the linear spatial distribution model, the wake vortices tracking algorithm was put proposed to estimate the wake track. First, the whole wake is regarded as a linear target of joint motion, the function between measurement likelihood and wake states such as center, slope angle, and length is got, and it is helpful to carry out data association when the wake measurement number changed and in dense multi-return environments. Then, the states of the whole wake were estimated using particle filtering. Simulation results show that the proposed algorithm can accurately estimates the real wake states in the condition of low-threshold detection. This research is helpful to the wake return identification using the wake vortex characteristics in airport application and early warning system.
2010, 26(10): 1560-1566.
Abstract：
An important technology in the area of Intelligent Vehicle(IV) is how to accurately calculate the angle between the moving orientation of the vehicle and the driveway, most of the literatures nowadays have a hypothesis that the optical axis of the camera is parallel to the ground, so the installation error of the camera has been neglected. This paper achieved the angle detection between the moving orientation of the vehicle and the driveway based on monocular vision, detailed technical realization scenario has been given, and we emphatically analyzed the rectification method under the circumstance of there is an angle between the optical axis of the camera and the ground, by using our method, the effect of the installation error towards the detection results can be greatly decreased, so this paper has broaden the application scope of angle detection technique and has made it become more robust, images captured from the real scene also validated the accuracy of our method.
An important technology in the area of Intelligent Vehicle(IV) is how to accurately calculate the angle between the moving orientation of the vehicle and the driveway, most of the literatures nowadays have a hypothesis that the optical axis of the camera is parallel to the ground, so the installation error of the camera has been neglected. This paper achieved the angle detection between the moving orientation of the vehicle and the driveway based on monocular vision, detailed technical realization scenario has been given, and we emphatically analyzed the rectification method under the circumstance of there is an angle between the optical axis of the camera and the ground, by using our method, the effect of the installation error towards the detection results can be greatly decreased, so this paper has broaden the application scope of angle detection technique and has made it become more robust, images captured from the real scene also validated the accuracy of our method.
2010, 26(10): 1567-1572.
Abstract：
Copy and paste-type form (Copy-Move) of tampering with the digital image is that copies the part of the region and pastes it into another area with an image. This way is in order to achieve the removal of the important contents of an image. It is a simple and effective technology of the image tampering. In response to this distorted way, this paper presents a blind detection method that detects the correlation of the image feature pixel. In order to remove the little noises and reduce the computational complexity, this paper also use the DTCWT accuracy in the image, then calculates the threshold of the image blocks, the last calculate the correlation of the image blocks. The experimental result indicates that tampering authentication method proposed in this paper can effectively combat the impact of noise on the certification; this approach has the good robust to the general noise such as Gaussian noise and low frequency filter.
Copy and paste-type form (Copy-Move) of tampering with the digital image is that copies the part of the region and pastes it into another area with an image. This way is in order to achieve the removal of the important contents of an image. It is a simple and effective technology of the image tampering. In response to this distorted way, this paper presents a blind detection method that detects the correlation of the image feature pixel. In order to remove the little noises and reduce the computational complexity, this paper also use the DTCWT accuracy in the image, then calculates the threshold of the image blocks, the last calculate the correlation of the image blocks. The experimental result indicates that tampering authentication method proposed in this paper can effectively combat the impact of noise on the certification; this approach has the good robust to the general noise such as Gaussian noise and low frequency filter.
2010, 26(10): 1573-1576.
Abstract：
Because the frequency estimate precision of Rife algorithm has a great deviation when the signal real frequency is near to the discrete frequency, but the frequency estimate precision can reach Cramer-Rao lower bound when the signal frequency is near to the midpoint of two neighboring discrete frequencies. An improved Rife(I-Rife) algorithm is presented by moving the signal frequency to the midpoint area of two neighboring discrete frequencies and then the frequency is estimated by Rife algorithm. The ill-judged probability of correctional frequency direction can decrease sharply after using improved criterion. The I-Rife algorithm holds on higher precision even when the SNR reaches to-13dB, but it need lower workload owing to using spectrum subdivision technique. The simulation results indicate that I-Rife algorithm not only has good frequency estimation precision, but also has a good stability in all frequency domains. Frequency estimation of sinusoid wave based on the I-Rife algorithm can be achieved in real-time. It can be implemented easily by the hardware.
Because the frequency estimate precision of Rife algorithm has a great deviation when the signal real frequency is near to the discrete frequency, but the frequency estimate precision can reach Cramer-Rao lower bound when the signal frequency is near to the midpoint of two neighboring discrete frequencies. An improved Rife(I-Rife) algorithm is presented by moving the signal frequency to the midpoint area of two neighboring discrete frequencies and then the frequency is estimated by Rife algorithm. The ill-judged probability of correctional frequency direction can decrease sharply after using improved criterion. The I-Rife algorithm holds on higher precision even when the SNR reaches to-13dB, but it need lower workload owing to using spectrum subdivision technique. The simulation results indicate that I-Rife algorithm not only has good frequency estimation precision, but also has a good stability in all frequency domains. Frequency estimation of sinusoid wave based on the I-Rife algorithm can be achieved in real-time. It can be implemented easily by the hardware.
2010, 26(10): 1577-1582.
Abstract：
In this paper, a new evaluation method for synthetic aperture radar (SAR) jamming is proposed. This method is mainly based on the concept of structure similarity index and it’s characteristic feature is consistent with perceptual property of human visual system (HVS). Firstly the jammed image and the primitive image are wavelets decomposed; secondly structure similarities are calculated for each subband in wavelet domain and each subbands’ structure similarity is weighted by contrast sensitivity function; at last it comes to the final evaluation index by summing up all weighted structure similarities. Simulation results shows that this index can not only measure the amount of the disturbance between the jammed and the primitive SAR image, but also reflect how people’s subjective feelings to the image quality in a better way compared with ordinary evaluation index, and reflect the difference of information loss when the interfere energy distributes in different regions in the image.
In this paper, a new evaluation method for synthetic aperture radar (SAR) jamming is proposed. This method is mainly based on the concept of structure similarity index and it’s characteristic feature is consistent with perceptual property of human visual system (HVS). Firstly the jammed image and the primitive image are wavelets decomposed; secondly structure similarities are calculated for each subband in wavelet domain and each subbands’ structure similarity is weighted by contrast sensitivity function; at last it comes to the final evaluation index by summing up all weighted structure similarities. Simulation results shows that this index can not only measure the amount of the disturbance between the jammed and the primitive SAR image, but also reflect how people’s subjective feelings to the image quality in a better way compared with ordinary evaluation index, and reflect the difference of information loss when the interfere energy distributes in different regions in the image.
2010, 26(10): 1583-1587.
Abstract：
Space-borne ISAR imaging technology has been regarded and studied gradually all over the world. The works are carried out in the paper aimed at a problem of mass data when some returned signal information is transmitted to the processors on the ground by spaceborne ISAR. A new method of ISAR data compressing and reconstruction based on Compressive Sensing (CS) is proposed. In the method, the returned signal is transformed spectrogram field which is range-slow time field, and the spectrogram is transmitted after it is compressed by using CS technology. Thus, the transmitted data can be reduced apparently. Next, the spectrogram information is recovered by using the orthogonal matching algorithm, and the ISAR image is reconstructed by using the method in the paper. Simulation results show that the reconstructed spectrogram is quite similar to the spectrogram uncompressed, and the fine ISAR image can be achieved by reconstructing. These works support a new idea to reduce data, improve efficiency in the ISAR signal processing.
Space-borne ISAR imaging technology has been regarded and studied gradually all over the world. The works are carried out in the paper aimed at a problem of mass data when some returned signal information is transmitted to the processors on the ground by spaceborne ISAR. A new method of ISAR data compressing and reconstruction based on Compressive Sensing (CS) is proposed. In the method, the returned signal is transformed spectrogram field which is range-slow time field, and the spectrogram is transmitted after it is compressed by using CS technology. Thus, the transmitted data can be reduced apparently. Next, the spectrogram information is recovered by using the orthogonal matching algorithm, and the ISAR image is reconstructed by using the method in the paper. Simulation results show that the reconstructed spectrogram is quite similar to the spectrogram uncompressed, and the fine ISAR image can be achieved by reconstructing. These works support a new idea to reduce data, improve efficiency in the ISAR signal processing.
2010, 26(10): 1588-1594.
Abstract：
The geometric rectification method based on SAR image simulation, with advantages of no requirement to the ground control points (GCP) and precise imaging parameters and of that all the processing can be done automatically, has been gotten broad attention and used widely. However, the input parameters of SAR image simulation (such as the course angle, flying height, near slant range, digital elevation model data, etc) bear errors since the measuring equipments are imprecise. This will change the feature of the simulated SAR image, and cause the error of the image matching parameter (such as GCP precision) at worst, and then reduce the geometric correction precision. This paper analyzed the influence of the input parameters and GCP in the SAR image simulation and image matching. Furthermore, the error impaction of parameters was analyzed completely, and the corresponding calculation formula was also derived. The vacancy left over in current papers has been filled.
The geometric rectification method based on SAR image simulation, with advantages of no requirement to the ground control points (GCP) and precise imaging parameters and of that all the processing can be done automatically, has been gotten broad attention and used widely. However, the input parameters of SAR image simulation (such as the course angle, flying height, near slant range, digital elevation model data, etc) bear errors since the measuring equipments are imprecise. This will change the feature of the simulated SAR image, and cause the error of the image matching parameter (such as GCP precision) at worst, and then reduce the geometric correction precision. This paper analyzed the influence of the input parameters and GCP in the SAR image simulation and image matching. Furthermore, the error impaction of parameters was analyzed completely, and the corresponding calculation formula was also derived. The vacancy left over in current papers has been filled.
2010, 26(10): 1595-1600.
Abstract：
The successive interference cancellation (SIC) receiver is widely used in the Multi-Input-Multi-Output (MIMO) system as a signal detection technology. In the SIC receiver, the decision error of the detected streams will impact the accuracy of the undetected streams, which will bring in residual multi-stream interference and cause the error diffusion problem. In this paper, a minimum mean square error-ordered successive interference cancellation (MMSE-OSIC) receiver with soft decision (SD) is presented. In the proposed SD-MMSE-OSIC receiver, the soft decision instead of the hard decision is used for interference regeneration and cancellation, which can efficiently prevent the error diffusion problem of the hard decision (HD) based MMSEOSIC receiver. We also propose a method to estimate the power of the residual multi-stream interference, with which we can accurately estimate the signal-to-interference-and-noise ratio (SINR) of each stream, which is usually overestimated in the HD based MMSE-OSIC receiver. In the proposed receiver, the soft decision method with higher reliability is utilized to minimize the residual multi-stream interference, while the accurate estimation of SINR helps to mitigate the impact of the residual interference on the undetected streams, thus fewer error diffusion problems are assured. Simulation results show that the proposed SD-MMSE-OSIC receiver significantly outperforms the linear MMSE receiver and the hard decision based MMSE-OSIC receiver.
The successive interference cancellation (SIC) receiver is widely used in the Multi-Input-Multi-Output (MIMO) system as a signal detection technology. In the SIC receiver, the decision error of the detected streams will impact the accuracy of the undetected streams, which will bring in residual multi-stream interference and cause the error diffusion problem. In this paper, a minimum mean square error-ordered successive interference cancellation (MMSE-OSIC) receiver with soft decision (SD) is presented. In the proposed SD-MMSE-OSIC receiver, the soft decision instead of the hard decision is used for interference regeneration and cancellation, which can efficiently prevent the error diffusion problem of the hard decision (HD) based MMSEOSIC receiver. We also propose a method to estimate the power of the residual multi-stream interference, with which we can accurately estimate the signal-to-interference-and-noise ratio (SINR) of each stream, which is usually overestimated in the HD based MMSE-OSIC receiver. In the proposed receiver, the soft decision method with higher reliability is utilized to minimize the residual multi-stream interference, while the accurate estimation of SINR helps to mitigate the impact of the residual interference on the undetected streams, thus fewer error diffusion problems are assured. Simulation results show that the proposed SD-MMSE-OSIC receiver significantly outperforms the linear MMSE receiver and the hard decision based MMSE-OSIC receiver.
