2010 Vol. 26 No. 2
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2010, 26(2): 161-165.
Abstract：
According to the directional property and coefficients energy feature in contourlet decomposition, we proposed a new algorithm which is adapted to extract the texture’s features. The proposed method gets the directional information by steerable filter and then gets texture features by contourlet decomposition. At last the directional feature and contourlet coefficients features are combined as texture’s feature. Because the number of contourlet decomposition level and directions can be easily modified, the number of features can be adapted to different applications. With the extracted feature vectors, we can easily distinguish different texture in standard Brodatz texture database with high classification accuracy.
According to the directional property and coefficients energy feature in contourlet decomposition, we proposed a new algorithm which is adapted to extract the texture’s features. The proposed method gets the directional information by steerable filter and then gets texture features by contourlet decomposition. At last the directional feature and contourlet coefficients features are combined as texture’s feature. Because the number of contourlet decomposition level and directions can be easily modified, the number of features can be adapted to different applications. With the extracted feature vectors, we can easily distinguish different texture in standard Brodatz texture database with high classification accuracy.
2010, 26(2): 166-169.
Abstract：
In traditional radar target tracking, only angle and range measurement data are used, and the tracking precision can not be further improved because of insufficient target information. In this paper, utilizing the high range resolution profile (HRRP) information of modern radar, a highperformance target tracking algorithm referred to as FAT-UKF is proposed. The algorithm is based on HRRP extentaided tracking model, and is implemented via advanced nonlinear filtering technology. The performance improvement of tracking comes from extra measurement information of target extent, which is inherently related with target motion state. Simulation results for typical application example show that the presented method not only has a high convergence speed, but also can effectively break through the tracking error lower bounds of traditional methods, thus to significantly improve the total performance of tracking system.
In traditional radar target tracking, only angle and range measurement data are used, and the tracking precision can not be further improved because of insufficient target information. In this paper, utilizing the high range resolution profile (HRRP) information of modern radar, a highperformance target tracking algorithm referred to as FAT-UKF is proposed. The algorithm is based on HRRP extentaided tracking model, and is implemented via advanced nonlinear filtering technology. The performance improvement of tracking comes from extra measurement information of target extent, which is inherently related with target motion state. Simulation results for typical application example show that the presented method not only has a high convergence speed, but also can effectively break through the tracking error lower bounds of traditional methods, thus to significantly improve the total performance of tracking system.
2010, 26(2): 170-174.
Abstract：
Multidimensional product codes are a kind of mature EEC(errorcorrecting codes) with good performance and agile code structure。A new style coded cooperation scheme based on multidimensional product codes is discussed particularly in this paper, which uses the different dimension parity bits to cooperate. This coded cooperation scheme can get large diversity gain. Multidimensional product codes with extended hamming codes are used in theory analysis and computer simulation, slow fading channel and fast fading channel are two kinds channel model. The result of simulation shows that: on slow fading channel, Bit Error Rate (BER) is 10-3, cooperation level is 50%, when the interuser SNR is larger than 10dB，large gain(>8dB) is obtained; on fast fading channel , coded cooperation make the user with worse uplink channel perform better. The coded cooperation will have better application, in view of its practicability and good performance.
Multidimensional product codes are a kind of mature EEC(errorcorrecting codes) with good performance and agile code structure。A new style coded cooperation scheme based on multidimensional product codes is discussed particularly in this paper, which uses the different dimension parity bits to cooperate. This coded cooperation scheme can get large diversity gain. Multidimensional product codes with extended hamming codes are used in theory analysis and computer simulation, slow fading channel and fast fading channel are two kinds channel model. The result of simulation shows that: on slow fading channel, Bit Error Rate (BER) is 10-3, cooperation level is 50%, when the interuser SNR is larger than 10dB，large gain(>8dB) is obtained; on fast fading channel , coded cooperation make the user with worse uplink channel perform better. The coded cooperation will have better application, in view of its practicability and good performance.
2010, 26(2): 175-179.
Abstract：
The formulation of a point target spectrum is a key step in deriving synthetic aperture radar focusing algorithms, which exploits the processing efficiency of the frequency domain. However, the existence of a double-square-root (DSR) in the bistatic range equation makes it difficult to find an exact analytical solution for the 2-D spectrum. In this paper, according to the idea of function optimal approach, we derive a new 2-D point target spectrum on the basis of Legendre polynomial expansion, which is more exact than the existing spectrums during the synthetic aperture time.
The formulation of a point target spectrum is a key step in deriving synthetic aperture radar focusing algorithms, which exploits the processing efficiency of the frequency domain. However, the existence of a double-square-root (DSR) in the bistatic range equation makes it difficult to find an exact analytical solution for the 2-D spectrum. In this paper, according to the idea of function optimal approach, we derive a new 2-D point target spectrum on the basis of Legendre polynomial expansion, which is more exact than the existing spectrums during the synthetic aperture time.
2010, 26(2): 180-183.
Abstract：
The rapid development of FPGA and its powerful parallel processing ability make it play more and more important role in SAR signal processing and some other high speed real time signal processing areas. This paper takes a spaceborne SAR signal storage and pretreatment system based on FPGA as an illustration, with modularization method, FPGA effectively realize the function of managing and controlling multichannel 2GB SAR signal memory, FIR filtering and downsampling. Of these modules, this paper emphasizes design and implementation of threeport SDRAM controller module and filtering and downsampling module.
The rapid development of FPGA and its powerful parallel processing ability make it play more and more important role in SAR signal processing and some other high speed real time signal processing areas. This paper takes a spaceborne SAR signal storage and pretreatment system based on FPGA as an illustration, with modularization method, FPGA effectively realize the function of managing and controlling multichannel 2GB SAR signal memory, FIR filtering and downsampling. Of these modules, this paper emphasizes design and implementation of threeport SDRAM controller module and filtering and downsampling module.
2010, 26(2): 184-189.
Abstract：
View synthesis framework based on cylindrical panoramic images is proposed, and image rectification and interpolation of cylindrical panoramic images are mainly investigated. Advantage of epiline sampling in rectification of cylindrical image is analyzed, and reference images are sampled efficiently and sufficiently by calculating the startend position, number, range of epiline. The approach of epiline sampling on cylindrical images is adopted in order to reduce image deformation, object distortion and resolution losing due to perspective transformation in some other algorithms. For novel view interpolation, according to the imaging model of cylindrical panoramic images, position and color calculation of pixels on novel view is formulated. Results of our approach applied to both synthetic and real scene are given at the end of this paper.
View synthesis framework based on cylindrical panoramic images is proposed, and image rectification and interpolation of cylindrical panoramic images are mainly investigated. Advantage of epiline sampling in rectification of cylindrical image is analyzed, and reference images are sampled efficiently and sufficiently by calculating the startend position, number, range of epiline. The approach of epiline sampling on cylindrical images is adopted in order to reduce image deformation, object distortion and resolution losing due to perspective transformation in some other algorithms. For novel view interpolation, according to the imaging model of cylindrical panoramic images, position and color calculation of pixels on novel view is formulated. Results of our approach applied to both synthetic and real scene are given at the end of this paper.
2010, 26(2): 190-196.
Abstract：
Ground based Space Surveillance Phased Array (SSPA) Radar usually works on the mode of multi-tasking and multi-objects, and radiates objects in time segmentations. Aiming at this point, taking the ballistic missile (BM) as an example, the multi-section time segmented radar returns model was developed in the paper. And then the micro-Doppler modulation characteristic induced by finned missiles’ spinning motion was analyzed. The feasibility of using microDoppler modulation period as an important feature parameter to recognize the BM target was opened out in theory. According to the characteristics of the multisection signals, the Radon-p-STFT method was proposed to estimate the half radial acceleration. Based on the acceleration compensated signal, the micro-Doppler modulation period was extracted successfully utilizing circular Average Magnitude Difference Function (AMDF).
Ground based Space Surveillance Phased Array (SSPA) Radar usually works on the mode of multi-tasking and multi-objects, and radiates objects in time segmentations. Aiming at this point, taking the ballistic missile (BM) as an example, the multi-section time segmented radar returns model was developed in the paper. And then the micro-Doppler modulation characteristic induced by finned missiles’ spinning motion was analyzed. The feasibility of using microDoppler modulation period as an important feature parameter to recognize the BM target was opened out in theory. According to the characteristics of the multisection signals, the Radon-p-STFT method was proposed to estimate the half radial acceleration. Based on the acceleration compensated signal, the micro-Doppler modulation period was extracted successfully utilizing circular Average Magnitude Difference Function (AMDF).
2010, 26(2): 197-202.
Abstract：
The amplitude modulation of rotating scatter centers on radar echo is investigated. Based on the above, a method of extracting space characteristics of rotating scatter centers through micromotion is proposed. At first, the spectra of echoes can be gained through temporalfrequency analysis. Then based on the microDoppler frequency difference, the scatter energy of each scatter center can be estimated through edge characteristics of spectra, which varies with time. Combined with estimating of micromotion parameters, the space characteristics of rotating scatter centers are extracted, which is validated by simulation and outdoor radar test. The space characteristics of rotating scatter centers can tell the structure information of rotating parts and improve the performance of target recognization.
The amplitude modulation of rotating scatter centers on radar echo is investigated. Based on the above, a method of extracting space characteristics of rotating scatter centers through micromotion is proposed. At first, the spectra of echoes can be gained through temporalfrequency analysis. Then based on the microDoppler frequency difference, the scatter energy of each scatter center can be estimated through edge characteristics of spectra, which varies with time. Combined with estimating of micromotion parameters, the space characteristics of rotating scatter centers are extracted, which is validated by simulation and outdoor radar test. The space characteristics of rotating scatter centers can tell the structure information of rotating parts and improve the performance of target recognization.
2010, 26(2): 203-207.
Abstract：
There are diverse kinds of sensors can be used for space objects recognition, such as radar, radio, IR sensors and electrooptical sensors. The information acquired by them is redundant and complemental in time domain, frequency domain or characteristic domain. The redundant information can improve the recognition reliability of fusion method and the complemental information can span the time or space range that the objects can be recognized. Various kinds of classifiers are designed to the complex space objects recognition problem, the automatic optimization and assemble of them is the key factor for the good performance of the whole fusion system. In this paper, the traits of each kind of sensors in the distributed heterogeneous sensor information process system are analyzed specially, and then a multilevel enhanced fusion scheme for space objects recognition is brought out to exploit latent abilities of various kinds of classifiers and the software design of systematical level is presented. The scheme assembles different sensors and fusion classifiers automatically so as to exploit the latent abilities of various kinds of classifiers and to improve the efficiency and robustness of the system.
There are diverse kinds of sensors can be used for space objects recognition, such as radar, radio, IR sensors and electrooptical sensors. The information acquired by them is redundant and complemental in time domain, frequency domain or characteristic domain. The redundant information can improve the recognition reliability of fusion method and the complemental information can span the time or space range that the objects can be recognized. Various kinds of classifiers are designed to the complex space objects recognition problem, the automatic optimization and assemble of them is the key factor for the good performance of the whole fusion system. In this paper, the traits of each kind of sensors in the distributed heterogeneous sensor information process system are analyzed specially, and then a multilevel enhanced fusion scheme for space objects recognition is brought out to exploit latent abilities of various kinds of classifiers and the software design of systematical level is presented. The scheme assembles different sensors and fusion classifiers automatically so as to exploit the latent abilities of various kinds of classifiers and to improve the efficiency and robustness of the system.
2010, 26(2): 208-212.
Abstract：
An efficient method is proposed for the realization of high resolution spectrum estimation and weak signals detection in broadband reconnaissance receiver. The broadband input signal is first divided into several equivalent narrow bands using digital channelized receiver, and the subband spectrums formed by FFT respectively is ranked to recompose the whole spectrum of the input signal. Noise floor is estimated by morphologic operation to correct the spectrum. Signal detection is performed by comparing the corrected spectrum line and the adaptive threshold estimated based on the distribution characteristic of the noise spectrum lines. Analysis and simulation results show the effectiveness of the proposed method.
An efficient method is proposed for the realization of high resolution spectrum estimation and weak signals detection in broadband reconnaissance receiver. The broadband input signal is first divided into several equivalent narrow bands using digital channelized receiver, and the subband spectrums formed by FFT respectively is ranked to recompose the whole spectrum of the input signal. Noise floor is estimated by morphologic operation to correct the spectrum. Signal detection is performed by comparing the corrected spectrum line and the adaptive threshold estimated based on the distribution characteristic of the noise spectrum lines. Analysis and simulation results show the effectiveness of the proposed method.
2010, 26(2): 213-218.
Abstract：
Polarimetric detection models are established for monopulse detection of rangeextended nonfluctuation targets and Rayleigh fluctuation targets. The corresponding polarimetric detectors are derived, and their detection performance is analytically expressed. Then the relationships between the detection performance and the radar bandwidth, polarization of the target’s echoes, and estimation error of the target’s radial scale are theoretically analyzed, and the detection algorithms proposed in this paper are compared with the polarimetric detection algorithm using binary integration. The results show that, an optimal bandwidth maximizing the detection probability of a Rayleigh target can be found for a given signal-to-noise ratio. The detection performance difference of deterministicallypolarized targets and randomlypolarized targets is remarkable when the radar bandwidth is narrow. When the radar bandwidth is wide, the detection of a randomlypolarized target has a performance loss of about 1.3dB in contrast with the detection of a deterministicallypolarized target. For a Rayleigh target, the detection performance is more sensitive to the underestimate than to the overestimate of the target’s radial scale. The detection performance of binary integration is generally inferior to the detection performance of radial integration, but the performance difference between them is relatively small.
Polarimetric detection models are established for monopulse detection of rangeextended nonfluctuation targets and Rayleigh fluctuation targets. The corresponding polarimetric detectors are derived, and their detection performance is analytically expressed. Then the relationships between the detection performance and the radar bandwidth, polarization of the target’s echoes, and estimation error of the target’s radial scale are theoretically analyzed, and the detection algorithms proposed in this paper are compared with the polarimetric detection algorithm using binary integration. The results show that, an optimal bandwidth maximizing the detection probability of a Rayleigh target can be found for a given signal-to-noise ratio. The detection performance difference of deterministicallypolarized targets and randomlypolarized targets is remarkable when the radar bandwidth is narrow. When the radar bandwidth is wide, the detection of a randomlypolarized target has a performance loss of about 1.3dB in contrast with the detection of a deterministicallypolarized target. For a Rayleigh target, the detection performance is more sensitive to the underestimate than to the overestimate of the target’s radial scale. The detection performance of binary integration is generally inferior to the detection performance of radial integration, but the performance difference between them is relatively small.
2010, 26(2): 219-224.
Abstract：
The combination of orthogonal frequency division multiplexing (OFDM) and bit-interleaved coded modulation (BICM) is known as an efficient technique to combat frequency selective fading. Significant performance degradation can result from carrier frequency offset ,which caused Inter Carrier Interference(ICI). Based on Maximum Likelihood（ML）algorithm , an itertive frequency offset estimation algorithm for BICM-OFDM system is proposed. This algorithm makes full use of the information provided by decoder,and has two steps. Firstly, the initial estimation employs the conventional ML algorithm,then, the rudimental frequency offset can be obtained by hard-decision information provided by BICM decoder. The precision could be improve by the feedback information that provided by iterative decoder of BICM. Through the wideband HF channel,the simulation results show that, in the range between 0 and 0.2,the proposed algorithm efficiently estimates frequency offset after three iterations. The proposed algorithm improves the accuracy of frequency offset estimation with low SNR and improves the range of frequency offset estimation compared with the conventional ML algorithm.
The combination of orthogonal frequency division multiplexing (OFDM) and bit-interleaved coded modulation (BICM) is known as an efficient technique to combat frequency selective fading. Significant performance degradation can result from carrier frequency offset ,which caused Inter Carrier Interference(ICI). Based on Maximum Likelihood（ML）algorithm , an itertive frequency offset estimation algorithm for BICM-OFDM system is proposed. This algorithm makes full use of the information provided by decoder,and has two steps. Firstly, the initial estimation employs the conventional ML algorithm,then, the rudimental frequency offset can be obtained by hard-decision information provided by BICM decoder. The precision could be improve by the feedback information that provided by iterative decoder of BICM. Through the wideband HF channel,the simulation results show that, in the range between 0 and 0.2,the proposed algorithm efficiently estimates frequency offset after three iterations. The proposed algorithm improves the accuracy of frequency offset estimation with low SNR and improves the range of frequency offset estimation compared with the conventional ML algorithm.
2010, 26(2): 225-229.
Abstract：
Taking advantage of the complementary characteristics in synthetic aperture radar (SAR) and optical images, a military target detection method based on decision fusion of regions of interest (ROI) is proposed. The algorithm firstly extracts ROI from SAR and optical images respectively, and then assigns reliability degrees, which indicated the probability of target, to ROI based on their statistical features and geometric features. Finally, the reliability degrees of the same ROI from two sources are combined by D-S decision level fusion theory before an ultimate detection result is obtained. The method makes good complementary of the advantages of SAR and optical images, which is validated in the experiments with remote sensing image set.
Taking advantage of the complementary characteristics in synthetic aperture radar (SAR) and optical images, a military target detection method based on decision fusion of regions of interest (ROI) is proposed. The algorithm firstly extracts ROI from SAR and optical images respectively, and then assigns reliability degrees, which indicated the probability of target, to ROI based on their statistical features and geometric features. Finally, the reliability degrees of the same ROI from two sources are combined by D-S decision level fusion theory before an ultimate detection result is obtained. The method makes good complementary of the advantages of SAR and optical images, which is validated in the experiments with remote sensing image set.
2010, 26(2): 230-233.
Abstract：
The paper has proposed a spatial spectrum estimation method based on the spatial filtering approach. After the overlap subarrays are set in the array, the spatial jamming signals have been filtered and restrained using the adaptive beam formed by the subarray and the SINR is increased for the desired signal. Based on the secondary combination of the subarrays, the direction-of-arrivals are estimated with the outputs of the subarrays and the locations of the subarrays using the spatial spectrum estimation method in the desired spatial regions. Simulation results show the spatial spectrum estimation method based on the spatial filtering approach has improved the electromagnetic environment for the desired signal and the estimate accuracy and the antijamming ability achieved are better than regular spatial spectrum estimation method.
The paper has proposed a spatial spectrum estimation method based on the spatial filtering approach. After the overlap subarrays are set in the array, the spatial jamming signals have been filtered and restrained using the adaptive beam formed by the subarray and the SINR is increased for the desired signal. Based on the secondary combination of the subarrays, the direction-of-arrivals are estimated with the outputs of the subarrays and the locations of the subarrays using the spatial spectrum estimation method in the desired spatial regions. Simulation results show the spatial spectrum estimation method based on the spatial filtering approach has improved the electromagnetic environment for the desired signal and the estimate accuracy and the antijamming ability achieved are better than regular spatial spectrum estimation method.
2010, 26(2): 234-240.
Abstract：
A novel approach using bayesian network is proposed for local semantic modeling of natural scenes. Directions of region’s neighborhood and adjacent region’s semantics are involved in the structure of the bayesian network. Image representation is formed by the local sematic descriptors for categorization of scenes. Parameters of the bayesian network are learned using the training set with manual annotation. For test images, the probability of the regions’ semantic is infered by the bayesian network based on the lowlevel features as well as the semantics of adjacent regions. The final annotation result of whole image regions is approached by iterations through th network. Images are represented through the frequency of occurrence of the local semantic objects. Experiment conducted on natural scenes’ dataset demonstrate the effectiveness and effciency of the proposed approach for local semantic modeling and categorization of natural scenes.
A novel approach using bayesian network is proposed for local semantic modeling of natural scenes. Directions of region’s neighborhood and adjacent region’s semantics are involved in the structure of the bayesian network. Image representation is formed by the local sematic descriptors for categorization of scenes. Parameters of the bayesian network are learned using the training set with manual annotation. For test images, the probability of the regions’ semantic is infered by the bayesian network based on the lowlevel features as well as the semantics of adjacent regions. The final annotation result of whole image regions is approached by iterations through th network. Images are represented through the frequency of occurrence of the local semantic objects. Experiment conducted on natural scenes’ dataset demonstrate the effectiveness and effciency of the proposed approach for local semantic modeling and categorization of natural scenes.
2010, 26(2): 241-246.
Abstract：
This paper proposes an adaptive modulation algorithm to realize unequal error protection (UEP) transmission in data spread Orthogonal Frequency Division Multiplexing (OFDM) systems. Based on the fact that the original data symbols have the same transmission characteristic, we respectively research an UEP algorithm to maximize the transmission rate with given power restriction aiming at increasing channel capacity, and an UEP algorithm to minimize the transmission power with given rate restriction aiming at satisfying the users’ requirements. Both algorithms can guarantee the different transmission qualities and different transmission rates of different priority data, according to the data’s requirements. The simulation results indicate that the maximizing rate UEP algorithm can ensure the transmission quality requirements with maximal rate, as well as the minimizing power UEP algorithm can ensure the transmission quality requirements with minimum power. The results of comparison with corresponding traditional OFDM algorithms show that data spread UEP algorithm can reduce algorithm complexity greatly, can decrease the modulation parameters transfer evidently, and can balance between performance and complexity, thus it has better application value.
This paper proposes an adaptive modulation algorithm to realize unequal error protection (UEP) transmission in data spread Orthogonal Frequency Division Multiplexing (OFDM) systems. Based on the fact that the original data symbols have the same transmission characteristic, we respectively research an UEP algorithm to maximize the transmission rate with given power restriction aiming at increasing channel capacity, and an UEP algorithm to minimize the transmission power with given rate restriction aiming at satisfying the users’ requirements. Both algorithms can guarantee the different transmission qualities and different transmission rates of different priority data, according to the data’s requirements. The simulation results indicate that the maximizing rate UEP algorithm can ensure the transmission quality requirements with maximal rate, as well as the minimizing power UEP algorithm can ensure the transmission quality requirements with minimum power. The results of comparison with corresponding traditional OFDM algorithms show that data spread UEP algorithm can reduce algorithm complexity greatly, can decrease the modulation parameters transfer evidently, and can balance between performance and complexity, thus it has better application value.
2010, 26(2): 247-254.
Abstract：
The problem of linear spatial precoding design is investigated for multipleantenna systems in frequency selective channels. For block transmission systems using cyclic prefix, it is shown that the linear spatial precoding design problem is equivalent to design one common spatial precoding for multiple adjacent frequency points, which can be numerically solved by convex optimization. Then a low-complexity suboptimal precoding aimed at maximizing the upper bound of channel capacity is proposed, which degenerates to the existing eigen-beamforming (EBF) when the equal power allocation is used. For non-block transmission systems, the drawbacks of EBF are analyzed. Then a novel algorithm based on successive searching, called successive EBF (SS-EBF), is proposed, which has a significant performance gain over EBF for high signal-to-noise ratio (SNR).
The problem of linear spatial precoding design is investigated for multipleantenna systems in frequency selective channels. For block transmission systems using cyclic prefix, it is shown that the linear spatial precoding design problem is equivalent to design one common spatial precoding for multiple adjacent frequency points, which can be numerically solved by convex optimization. Then a low-complexity suboptimal precoding aimed at maximizing the upper bound of channel capacity is proposed, which degenerates to the existing eigen-beamforming (EBF) when the equal power allocation is used. For non-block transmission systems, the drawbacks of EBF are analyzed. Then a novel algorithm based on successive searching, called successive EBF (SS-EBF), is proposed, which has a significant performance gain over EBF for high signal-to-noise ratio (SNR).
2010, 26(2): 255-261.
Abstract：
In this paper, we propose an efficient highlyparallel decoder architecture for quasi-cyclic (QC) low-density paritycheck (LDPC) codes, which leads to reduction in hardware complexity. Generally, QC-LDPC codes cannot be used to design a efficient highly-parallel decoding architecture for highthroughput applications. The QC-LDPC code parity matrix structure is exploited to parallelize the row and column decoding operations. Using this architecture, we have implemented a decoder for a (8176,7154) Finite geometry-based QC-LDPC code on a Xilinx Virtex-5 LX330 FPGA, and achieved decoding throughput of 800 Mbps with 15 fixed iterations.
In this paper, we propose an efficient highlyparallel decoder architecture for quasi-cyclic (QC) low-density paritycheck (LDPC) codes, which leads to reduction in hardware complexity. Generally, QC-LDPC codes cannot be used to design a efficient highly-parallel decoding architecture for highthroughput applications. The QC-LDPC code parity matrix structure is exploited to parallelize the row and column decoding operations. Using this architecture, we have implemented a decoder for a (8176,7154) Finite geometry-based QC-LDPC code on a Xilinx Virtex-5 LX330 FPGA, and achieved decoding throughput of 800 Mbps with 15 fixed iterations.
2010, 26(2): 262-266.
Abstract：
A bispcetrum based method of time-delay estimation is used for the flowmeter in the oil well. The accuracy of the flowmeter in the oil well is determined by the accuracy of time-delay estimation. When we use the cross-correlation method, high accuracy could not be achieved in existence of correlated Gaussian noise. However, because the bispcetrum based method of time-delay estimation could theoretically eliminate Gaussian noise, we use the bispcetrum method as the substitution of the cross-correlation method. Both simulation and analysis of data acquired by the ultrasonic flowmeter prototype are implemented to reveal the differences between bispectrum based method and cross-correlation method.
A bispcetrum based method of time-delay estimation is used for the flowmeter in the oil well. The accuracy of the flowmeter in the oil well is determined by the accuracy of time-delay estimation. When we use the cross-correlation method, high accuracy could not be achieved in existence of correlated Gaussian noise. However, because the bispcetrum based method of time-delay estimation could theoretically eliminate Gaussian noise, we use the bispcetrum method as the substitution of the cross-correlation method. Both simulation and analysis of data acquired by the ultrasonic flowmeter prototype are implemented to reveal the differences between bispectrum based method and cross-correlation method.
2010, 26(2): 267-271.
Abstract：
The space information processing systems based VLSI are easily suffered by SEU (Single Event Upset) .TMR (Three Module Redundancy) based structure redundancy and EDAC (Error Detection and Correction) based information redundancy are two kinds of system level faulttolerance methods for SEU. These methods are widely used in space aircraft electronic system. Simulation and analysis are implemented from four aspects: reliability, storage resource, hardware implement spending and time delay. The results show that EDAC is efficient when the data is long, the storage resource is limited and the demand of realtime performance is not high, however the TMR is efficient when the data is short, the storage resource is enough and the desire of realtime performance is high.
The space information processing systems based VLSI are easily suffered by SEU (Single Event Upset) .TMR (Three Module Redundancy) based structure redundancy and EDAC (Error Detection and Correction) based information redundancy are two kinds of system level faulttolerance methods for SEU. These methods are widely used in space aircraft electronic system. Simulation and analysis are implemented from four aspects: reliability, storage resource, hardware implement spending and time delay. The results show that EDAC is efficient when the data is long, the storage resource is limited and the demand of realtime performance is not high, however the TMR is efficient when the data is short, the storage resource is enough and the desire of realtime performance is high.
2010, 26(2): 272-276.
Abstract：
Time-interleaving is an efficient approach to increase the sampling rate of ∑Δ modulators, but time-interleaved(TI) ∑Δ modulators are sensitive to channel mismatch. Recently, a solution for this problem has been proposed with a zero of z=-1 and its corresponding pole in the noise transfer function. Based on the proposed second-order two-channel TI modulator, an approach of system optimization design is presented for high-order two-channel TI modulators. The system stability and optimization of zeros/poles are considered. As an example, a system of high-order two-channel TI ∑Δ modulator is designed with bandwidth of 4 MHz, which is suitable for application of digital video broadcasting-terrestrial (DVBT). Simulation results show that the proposed ∑Δ modulator has a large input signal range and is insensitive to channel mismatch.
Time-interleaving is an efficient approach to increase the sampling rate of ∑Δ modulators, but time-interleaved(TI) ∑Δ modulators are sensitive to channel mismatch. Recently, a solution for this problem has been proposed with a zero of z=-1 and its corresponding pole in the noise transfer function. Based on the proposed second-order two-channel TI modulator, an approach of system optimization design is presented for high-order two-channel TI modulators. The system stability and optimization of zeros/poles are considered. As an example, a system of high-order two-channel TI ∑Δ modulator is designed with bandwidth of 4 MHz, which is suitable for application of digital video broadcasting-terrestrial (DVBT). Simulation results show that the proposed ∑Δ modulator has a large input signal range and is insensitive to channel mismatch.
2010, 26(2): 277-285.
Abstract：
In this paper, a new nonlinear nonsteady method for signal treatment is introduced in detail, which is valid and predominant. It is used to analysed the seismic wave.The EMD method and its process are presented through a great amount of data study. A range of good-shift of data is given from a lot of data analysis and the rule is given. When the frequency of combined sine wave is constant, the value of A2/A1 is very small, and it is over a limit; or the value of A2/A1 is large, and it is over a limit, EMD method is not applicable. When amplitude ratio of sine wave A2/A1 is constant, but the frequency varies, if the value of f2/f1 is very small, and it is over a limit; or the value of f2 is very close to f1, and the ratio f2/f1 is over a limit, the value of y is not able to be shifted by EMD method.
In this paper, a new nonlinear nonsteady method for signal treatment is introduced in detail, which is valid and predominant. It is used to analysed the seismic wave.The EMD method and its process are presented through a great amount of data study. A range of good-shift of data is given from a lot of data analysis and the rule is given. When the frequency of combined sine wave is constant, the value of A2/A1 is very small, and it is over a limit; or the value of A2/A1 is large, and it is over a limit, EMD method is not applicable. When amplitude ratio of sine wave A2/A1 is constant, but the frequency varies, if the value of f2/f1 is very small, and it is over a limit; or the value of f2 is very close to f1, and the ratio f2/f1 is over a limit, the value of y is not able to be shifted by EMD method.
2010, 26(2): 286-290.
Abstract：
Mixed LFM signal is everywhere in signal environments in practice, it is important to recognize it for electronic intelligence. The cross-terms of Wigner-Ville distribution resulting from mixed signals reduce its resolution. A new approach of eliminating the cross-terms based on independent component analysis is presented. The independent signal components were extracted via blind source separation. The cross-terms were reduced significantly based on joint diagonalisation of the time-frequency distribution matrices. The reconstructed Wigner-Ville distribution has good resolution. Each LFM signal components are recognized from mixed signals using Wigner-Hough transform. The relation between input SNR and output SNR is computed, the simulation results show that the new approach improves recognition performance and WHT can enhance the output SNR when sampling number is increased.
Mixed LFM signal is everywhere in signal environments in practice, it is important to recognize it for electronic intelligence. The cross-terms of Wigner-Ville distribution resulting from mixed signals reduce its resolution. A new approach of eliminating the cross-terms based on independent component analysis is presented. The independent signal components were extracted via blind source separation. The cross-terms were reduced significantly based on joint diagonalisation of the time-frequency distribution matrices. The reconstructed Wigner-Ville distribution has good resolution. Each LFM signal components are recognized from mixed signals using Wigner-Hough transform. The relation between input SNR and output SNR is computed, the simulation results show that the new approach improves recognition performance and WHT can enhance the output SNR when sampling number is increased.
2010, 26(2): 291-297.
Abstract：
For distributed spaceborne single-baseline SAR-GMTI systems, SAR-ATI and SAR-DPCA are the two ordinarily exploited clutter suppression and moving target detection techniques. Based on the signal model and statistical model of the two clutter cancellers, the detection performance of ATI and DPCA are analyzed and compared, with a consideration to the channel amplitude/phase unbalance error, time/frequency synchronization error and the influence of clutter and noise. Simulation experiments demonstrate that DPCA is better than ATI under the homogeneous area assumptions. Channel amplitude/phase unbalance error are important error to performance degradation. After some preprocessing steps, frequency synchronization error are not very serious.
For distributed spaceborne single-baseline SAR-GMTI systems, SAR-ATI and SAR-DPCA are the two ordinarily exploited clutter suppression and moving target detection techniques. Based on the signal model and statistical model of the two clutter cancellers, the detection performance of ATI and DPCA are analyzed and compared, with a consideration to the channel amplitude/phase unbalance error, time/frequency synchronization error and the influence of clutter and noise. Simulation experiments demonstrate that DPCA is better than ATI under the homogeneous area assumptions. Channel amplitude/phase unbalance error are important error to performance degradation. After some preprocessing steps, frequency synchronization error are not very serious.
2010, 26(2): 298-302.
Abstract：
A new variable order (or tap-length) algorithm is presented and applied to variable order adaptive lattice recursive least square filter. The adjustment of correlative parameters when updating the filter order is also discussed. The new algorithm compares timemean square errors of long and short filters in terms of decibel and employs adaptive taplength step size. It can update filter length and tap-weights fast at the same time before the tapweights converge, and converge to optimal order under noises of different magnitudes. The theory analysis and numerical simulation results verify the efficiency of new algorithm.
A new variable order (or tap-length) algorithm is presented and applied to variable order adaptive lattice recursive least square filter. The adjustment of correlative parameters when updating the filter order is also discussed. The new algorithm compares timemean square errors of long and short filters in terms of decibel and employs adaptive taplength step size. It can update filter length and tap-weights fast at the same time before the tapweights converge, and converge to optimal order under noises of different magnitudes. The theory analysis and numerical simulation results verify the efficiency of new algorithm.
2010, 26(2): 303-309.
Abstract：
Direction finding is an important component of Electronic Warfare (EW) system. The direction finding precision may directly affect signal sorting, identification, location and jamming decision etc. It is an urgent task to improve the direction finding precision. To solve the problems of time difference direction finding is sensitive to interference and noise, this paper proposes a novel blind source separation algorithm based on informational canonical correlation analysis firstly, and then use the algorithm to improve time difference direction finding performance. The simulation results suggest that the proposed algorithm is efficient and feasible.
Direction finding is an important component of Electronic Warfare (EW) system. The direction finding precision may directly affect signal sorting, identification, location and jamming decision etc. It is an urgent task to improve the direction finding precision. To solve the problems of time difference direction finding is sensitive to interference and noise, this paper proposes a novel blind source separation algorithm based on informational canonical correlation analysis firstly, and then use the algorithm to improve time difference direction finding performance. The simulation results suggest that the proposed algorithm is efficient and feasible.
2010, 26(2): 310-313.
Abstract：
In this paper, we study the error performance of Vertical Bell Labs layered Space-Time (V-BLAST) system using Maximum Likelihood (ML) receiver in the presence of correlated fading channel. Our analysis is based on the channel model of Virtual Channel Representation (VCR) form, which considers both the local scatters and non-local scatters. The Pairwise Error Probability (PEP) expression over VCR channel model is derived exactly. The approximated expression of the PEP for high signal-to-noise ratio (SNR) region is used to analyze the characteristics of the diversity order. Simulation results are given to corroborate the theoretical analysis.
In this paper, we study the error performance of Vertical Bell Labs layered Space-Time (V-BLAST) system using Maximum Likelihood (ML) receiver in the presence of correlated fading channel. Our analysis is based on the channel model of Virtual Channel Representation (VCR) form, which considers both the local scatters and non-local scatters. The Pairwise Error Probability (PEP) expression over VCR channel model is derived exactly. The approximated expression of the PEP for high signal-to-noise ratio (SNR) region is used to analyze the characteristics of the diversity order. Simulation results are given to corroborate the theoretical analysis.
2010, 26(2): 314-320.
Abstract：
Complexity pursuit is an extension of projection pursuit to time series data and the method is closely related to blind separation of timedependent source signals and independent component analysis (ICA). In this paper， we consider the estimation of the data model of ICA when Gaussian noise is present and the components are time dependent. The separation result is affected because existing blind source separation algorithms do not give the method to estimate the autoregressive coefficients. A novel algorithm for noisy complexity pursuit is proposed. The algorithm gives the method to estimate autoregressive coefficients. Computer stimulations with natural images and artificial signals indicate the validity of the proposed algorithm. Moreover， comparisons with existing blind source separation algorithms further show the better performance of the proposed algorithm.
Complexity pursuit is an extension of projection pursuit to time series data and the method is closely related to blind separation of timedependent source signals and independent component analysis (ICA). In this paper， we consider the estimation of the data model of ICA when Gaussian noise is present and the components are time dependent. The separation result is affected because existing blind source separation algorithms do not give the method to estimate the autoregressive coefficients. A novel algorithm for noisy complexity pursuit is proposed. The algorithm gives the method to estimate autoregressive coefficients. Computer stimulations with natural images and artificial signals indicate the validity of the proposed algorithm. Moreover， comparisons with existing blind source separation algorithms further show the better performance of the proposed algorithm.
