This paper presents a method for high resolution multiple source direction finding with an antenna array. Unlike previously developed algorithms, the proposed approach can achieve high resolution direction finding with only one receiver, thereby, offering significant hardware savings. The proposed approach requires the signal received by the antenna array to be pre-processed by a beamformer network where each of the beamformer output ports are sequentially sampled by a RF switch. As the power of each beamformer output port is a function of the array covariance matrix, we derive a Kronecker form that leads to an unique least squares estimates of the array covariance matrix using the power measured from all the beamformer output ports. With the array covariance matrix estimated, conventional high resolution DF algorithms can be applied to determine the direction of arrival estimation of the multiple sources impinging the antenna array.
{"title":"High resolution DF with a single channel receiver","authors":"C. See","doi":"10.1109/SSP.2001.955337","DOIUrl":"https://doi.org/10.1109/SSP.2001.955337","url":null,"abstract":"This paper presents a method for high resolution multiple source direction finding with an antenna array. Unlike previously developed algorithms, the proposed approach can achieve high resolution direction finding with only one receiver, thereby, offering significant hardware savings. The proposed approach requires the signal received by the antenna array to be pre-processed by a beamformer network where each of the beamformer output ports are sequentially sampled by a RF switch. As the power of each beamformer output port is a function of the array covariance matrix, we derive a Kronecker form that leads to an unique least squares estimates of the array covariance matrix using the power measured from all the beamformer output ports. With the array covariance matrix estimated, conventional high resolution DF algorithms can be applied to determine the direction of arrival estimation of the multiple sources impinging the antenna array.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"255 1","pages":"520-523"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83499193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The source detection problem in array processing can be considered as a test for the equality of eigenvalues. This approach is implemented through a multiple hypothesis procedure which compares all pairwise differences between eigenvalues. A resampling procedure is used to estimate the null distributions of the test statistics, an advantage for small sample sizes or non-Gaussian signals since traditional techniques such as the minimum description length (MDL) assume Gaussianity. Simulations show the increased performance of the test compared to the MDL for small samples or non-Gaussian signals, with a noticeable improvement over the more accurate sphericity test.
{"title":"Resampling based techniques for source detection in array processing","authors":"R. Brcich, A. Zoubir","doi":"10.1109/SSP.2001.955213","DOIUrl":"https://doi.org/10.1109/SSP.2001.955213","url":null,"abstract":"The source detection problem in array processing can be considered as a test for the equality of eigenvalues. This approach is implemented through a multiple hypothesis procedure which compares all pairwise differences between eigenvalues. A resampling procedure is used to estimate the null distributions of the test statistics, an advantage for small sample sizes or non-Gaussian signals since traditional techniques such as the minimum description length (MDL) assume Gaussianity. Simulations show the increased performance of the test compared to the MDL for small samples or non-Gaussian signals, with a noticeable improvement over the more accurate sphericity test.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"82 1","pages":"26-29"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88595219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Combined spatial and time-frequency signatures of signal arrivals at multi-antenna receivers has been used for effective nonstationary interference suppression in broadband communication platforms. This paper presents a performance analysis of subspace projection array processing techniques for suppression of frequency modulated (FM) jammers in GPS receivers. The FM jammers are instantaneous narrowband and have clear time-frequency ((t-f)) signatures that are distinct from the GPS C/A spread spectrum code. The paper assumes that the spatial signature of the jammer is accurately estimated, but its instantaneous frequency (IF) estimate, which provides the basis for construction of the jammer subspace exhibits zero-mean independent Gaussian errors. Simulation results comparing the effects of IF errors in a single and multi-antenna GPS receivers are provided.
{"title":"Performance analysis of subspace projection techniques for anti-jamming GPS using spatio-temporal interference signatures","authors":"M. Amin, Liang Zhao, A. Lindsey","doi":"10.1109/SSP.2001.955297","DOIUrl":"https://doi.org/10.1109/SSP.2001.955297","url":null,"abstract":"Combined spatial and time-frequency signatures of signal arrivals at multi-antenna receivers has been used for effective nonstationary interference suppression in broadband communication platforms. This paper presents a performance analysis of subspace projection array processing techniques for suppression of frequency modulated (FM) jammers in GPS receivers. The FM jammers are instantaneous narrowband and have clear time-frequency ((t-f)) signatures that are distinct from the GPS C/A spread spectrum code. The paper assumes that the spatial signature of the jammer is accurately estimated, but its instantaneous frequency (IF) estimate, which provides the basis for construction of the jammer subspace exhibits zero-mean independent Gaussian errors. Simulation results comparing the effects of IF errors in a single and multi-antenna GPS receivers are provided.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"56 1","pages":"361-364"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89378725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We prove that a MIMO (multiple input multiple output) blind deconvolution problem for n colored uncorrelated signals can be converted to n SIMO (single input multiple output) problems, using eigenvalue decomposition of a special covariance matrix, depending on L-dimensional parameter b, if appropriate covariance matrices have sets of eigenvalues with empty pairwise intersection. We present a sufficient condition for this conversion and discuss how to End such parameters. We prove that the parameters b for which this is possible, form an open subset of IR/sup L/, whose complement has a Lebesgue measure zero.
{"title":"Multichannel blind deconvolution of colored signals via eigenvalue decomposition","authors":"P. Georgiev, A. Cichocki","doi":"10.1109/SSP.2001.955275","DOIUrl":"https://doi.org/10.1109/SSP.2001.955275","url":null,"abstract":"We prove that a MIMO (multiple input multiple output) blind deconvolution problem for n colored uncorrelated signals can be converted to n SIMO (single input multiple output) problems, using eigenvalue decomposition of a special covariance matrix, depending on L-dimensional parameter b, if appropriate covariance matrices have sets of eigenvalues with empty pairwise intersection. We present a sufficient condition for this conversion and discuss how to End such parameters. We prove that the parameters b for which this is possible, form an open subset of IR/sup L/, whose complement has a Lebesgue measure zero.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"37 1","pages":"273-276"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90736594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The bispectrum. is a higher-order statistic and is known to be a useful tool for detecting non-linearity. A succinct example of its power to identify non-linear sound waves from broken bridge struts was given by Rivola and White (1998). As well as detecting non-linearity it has the further advantage that its magnitude and shape can be used to estimate the third order non-linear structure (Barnett and Wolff). When a time series is repeated (such as sound waves from a collection of bridge struts) Diggle and Al-Wasel (1997) showed how to produce a common spectrum and to estimate individual departures from this global quantity. The purpose of this paper is to extend this method to the bispectrum and give a summary of common non-linearity among repeated time series. We evaluate our method using data from a group of people speaking the letter 'A' and from one person repeatedly speaking this letter.
{"title":"On the estimation of common non-linearity among repeated time series","authors":"A. G. Barnett, R. Wolff","doi":"10.1109/SSP.2001.955316","DOIUrl":"https://doi.org/10.1109/SSP.2001.955316","url":null,"abstract":"The bispectrum. is a higher-order statistic and is known to be a useful tool for detecting non-linearity. A succinct example of its power to identify non-linear sound waves from broken bridge struts was given by Rivola and White (1998). As well as detecting non-linearity it has the further advantage that its magnitude and shape can be used to estimate the third order non-linear structure (Barnett and Wolff). When a time series is repeated (such as sound waves from a collection of bridge struts) Diggle and Al-Wasel (1997) showed how to produce a common spectrum and to estimate individual departures from this global quantity. The purpose of this paper is to extend this method to the bispectrum and give a summary of common non-linearity among repeated time series. We evaluate our method using data from a group of people speaking the letter 'A' and from one person repeatedly speaking this letter.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"3 1","pages":"437-439"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91299249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a novel algorithm for computing the eigenvector associated with either the largest or the smallest eigenvalue of a complex Hermitian matrix. This type of algorithm is required for direction of arrival (DOA) and frequency estimation. Necessary and sufficient conditions for convergence are proved, and simulations show the superior performance over traditional methods.
{"title":"A new algorithm for computing the extreme eigenvectors of a complex Hermitian matrix","authors":"J. Manton","doi":"10.1109/SSP.2001.955263","DOIUrl":"https://doi.org/10.1109/SSP.2001.955263","url":null,"abstract":"This paper presents a novel algorithm for computing the eigenvector associated with either the largest or the smallest eigenvalue of a complex Hermitian matrix. This type of algorithm is required for direction of arrival (DOA) and frequency estimation. Necessary and sufficient conditions for convergence are proved, and simulations show the superior performance over traditional methods.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"1 1","pages":"225-228"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89656928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a novel algorithm for the design and hardware reduction of a class of multiplier-less two-channel perfect reconstruction (PR) filter banks (FB) using sum-of-powers-of-two (SOPOT) coefficients. It minimizes a more realistic hardware cost, such as adder cells, subject to a prescribed output accuracy taking account of rounding and overflow effects, instead of using just the SOPOT terms as in conventional methods. Furthermore, by using multiplier blocks (MB) to implement the filters in the FBs, significant overall saving in hardware resources can be achieved. An effective random search algorithm is also proposed to solve the design problem, which is also applicable to PR IIR FBs with highly nonlinear objective functions. Perfect reconstruction multirate filter have important applications in signal analysis, signal coding and the design of wavelet bases.
{"title":"Efficient design of a class of multiplier-less perfect reconstruction two-channel filter banks and wavelets with prescribed output accuracy","authors":"C. Pun, S. Chan, K. Ho","doi":"10.1109/SSP.2001.955358","DOIUrl":"https://doi.org/10.1109/SSP.2001.955358","url":null,"abstract":"This paper proposes a novel algorithm for the design and hardware reduction of a class of multiplier-less two-channel perfect reconstruction (PR) filter banks (FB) using sum-of-powers-of-two (SOPOT) coefficients. It minimizes a more realistic hardware cost, such as adder cells, subject to a prescribed output accuracy taking account of rounding and overflow effects, instead of using just the SOPOT terms as in conventional methods. Furthermore, by using multiplier blocks (MB) to implement the filters in the FBs, significant overall saving in hardware resources can be achieved. An effective random search algorithm is also proposed to solve the design problem, which is also applicable to PR IIR FBs with highly nonlinear objective functions. Perfect reconstruction multirate filter have important applications in signal analysis, signal coding and the design of wavelet bases.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"255 1","pages":"599-602"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78210033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a method of blind source separation that jointly exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed correlation matrices of the observation data, each of which is evaluated at a different time-windowed data frame, to estimate the demixing matrix. We show that the method is quite robust with respect to the spatially correlated but temporally white noise. We also discuss the extension of some existing second-order blind source separation methods. Extensive numerical experiments confirm the validity of the proposed method.
{"title":"Blind separation of second-order nonstationary and temporally colored sources","authors":"Seungjin Choi, A. Cichocki, A. Belouchrani","doi":"10.1109/SSP.2001.955318","DOIUrl":"https://doi.org/10.1109/SSP.2001.955318","url":null,"abstract":"This paper presents a method of blind source separation that jointly exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed correlation matrices of the observation data, each of which is evaluated at a different time-windowed data frame, to estimate the demixing matrix. We show that the method is quite robust with respect to the spatially correlated but temporally white noise. We also discuss the extension of some existing second-order blind source separation methods. Extensive numerical experiments confirm the validity of the proposed method.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"97 1","pages":"444-447"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74982140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A recursive least squares (RLS) algorithm with selective modification of the system estimation covariance matrix is employed to track the rapidly changing components of system parameters. A new on-line wavelet detector is designed for accurately identifying the changing locations and the branches of changing parameters. Employing theses techniques, the tracking performance of the proposed algorithm to rapidly changing systems can be significantly improved.
{"title":"A new wavelet-based tracking algorithm for rapidly time-varying systems","authors":"Yuanjin Zheng, Zhiping Lin","doi":"10.1109/SSP.2001.955255","DOIUrl":"https://doi.org/10.1109/SSP.2001.955255","url":null,"abstract":"A recursive least squares (RLS) algorithm with selective modification of the system estimation covariance matrix is employed to track the rapidly changing components of system parameters. A new on-line wavelet detector is designed for accurately identifying the changing locations and the branches of changing parameters. Employing theses techniques, the tracking performance of the proposed algorithm to rapidly changing systems can be significantly improved.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"7 1","pages":"194-197"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73032567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the growing capacity demand in wireless communication systems, space division multiplexing and space-time processing by means of antenna arrays are becoming ever more attractive as a technology to improve system performance, especially for the reduction of multipath effects. This paper presents a new low complexity and high accuracy algorithm to estimate the multipath delays and direction of arrivals (DOAs) simultaneously in wireless communication systems. By using separable dimension correlation processing, the temporal and spatial signal subspaces are formed and the joint two dimensional delay/DOA estimation problem is separated into two simpler one dimensional estimations.
{"title":"A new algorithm for joint DOA and multipath delay estimation: separable dimension subspace method","authors":"J. Mao, B. Champagne, M. O'Droma, L. Ge","doi":"10.1109/SSP.2001.955333","DOIUrl":"https://doi.org/10.1109/SSP.2001.955333","url":null,"abstract":"With the growing capacity demand in wireless communication systems, space division multiplexing and space-time processing by means of antenna arrays are becoming ever more attractive as a technology to improve system performance, especially for the reduction of multipath effects. This paper presents a new low complexity and high accuracy algorithm to estimate the multipath delays and direction of arrivals (DOAs) simultaneously in wireless communication systems. By using separable dimension correlation processing, the temporal and spatial signal subspaces are formed and the joint two dimensional delay/DOA estimation problem is separated into two simpler one dimensional estimations.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"93 1","pages":"504-507"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74370853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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