Recursive and efficient estimation of polynomial-phase is considered here, with alternatives to the standard Gauss-Newton approach presented. We consider approximations of the likelihood and phase noise distribution to derive recursive approximate maximum likelihood and Bayesian estimators. Monte Carlo simulations indicate that these methods compare favourably with the Gauss-Newton scheme both in terms of computational expense and efficiency thresholds.
{"title":"Computationally efficient iterative refinement techniques for polynomial phase signals","authors":"S. Sando, D. Huang, T. Pettitt","doi":"10.1109/SSP.2001.955312","DOIUrl":"https://doi.org/10.1109/SSP.2001.955312","url":null,"abstract":"Recursive and efficient estimation of polynomial-phase is considered here, with alternatives to the standard Gauss-Newton approach presented. We consider approximations of the likelihood and phase noise distribution to derive recursive approximate maximum likelihood and Bayesian estimators. Monte Carlo simulations indicate that these methods compare favourably with the Gauss-Newton scheme both in terms of computational expense and efficiency thresholds.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"100 1","pages":"421-424"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76367457","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 method to detect infrared land mine signatures embedded in rotationally invariant colored noise. A common problem in statistical image processing is high dimensionality. This causes a need for large sets of training data. To overcome this, an alternative formulation of the generalized likelihood ratio test (GLRT) is presented. This formulation makes it possible to utilize the circular-symmetry, rendering a substantial decrease in model dimensionality and consequently, in the amount of training data needed. Simulations indicate that a significant gain in performance can be achieved compared to both the non-parameterized detector and the matched filter.
{"title":"Land mine detection in rotationally invariant noise fields","authors":"L. Svensson, M. Lundberg","doi":"10.1109/SSP.2001.955249","DOIUrl":"https://doi.org/10.1109/SSP.2001.955249","url":null,"abstract":"This paper proposes a method to detect infrared land mine signatures embedded in rotationally invariant colored noise. A common problem in statistical image processing is high dimensionality. This causes a need for large sets of training data. To overcome this, an alternative formulation of the generalized likelihood ratio test (GLRT) is presented. This formulation makes it possible to utilize the circular-symmetry, rendering a substantial decrease in model dimensionality and consequently, in the amount of training data needed. Simulations indicate that a significant gain in performance can be achieved compared to both the non-parameterized detector and the matched filter.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"17 1","pages":"170-173"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77856378","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 addresses the problem of building appropriate statistical models of the way the Internet appears from the point of view of congestion, to a transmission control protocol (TCP) sender. TCP is a mechanism for implementing full duplex, acknowledged, end-to-end transmission over an Internet protocol (IP) network. This work has been motivated by the TCP variant, the so-called Vegas implementation. TCP Vegas is really the first implementation to be based loosely on system theoretic ideas in the sense that it measures the segment round-trip times across the network to adjust its transmission rate. This paper develops a new linear system framework for TCP, and applies recursive prediction error identification techniques to specify statistical models which may be used to develop alternative control strategies. Network simulations are used to illustrate behaviour.
{"title":"Internet transport layer system identification","authors":"L. White","doi":"10.1109/SSP.2001.955294","DOIUrl":"https://doi.org/10.1109/SSP.2001.955294","url":null,"abstract":"This paper addresses the problem of building appropriate statistical models of the way the Internet appears from the point of view of congestion, to a transmission control protocol (TCP) sender. TCP is a mechanism for implementing full duplex, acknowledged, end-to-end transmission over an Internet protocol (IP) network. This work has been motivated by the TCP variant, the so-called Vegas implementation. TCP Vegas is really the first implementation to be based loosely on system theoretic ideas in the sense that it measures the segment round-trip times across the network to adjust its transmission rate. This paper develops a new linear system framework for TCP, and applies recursive prediction error identification techniques to specify statistical models which may be used to develop alternative control strategies. Network simulations are used to illustrate behaviour.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"40 1","pages":"349-352"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76181316","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}
Summary form only given, as follows. Detection algorithms, whose design takes into account prior knowledge about the signals and the channel, face a quandary: they provide marked improvement in performance when the field operating conditions match well this available knowledge; but they experience strong degradation when the actual conditions depart from the assumed ones. In other words, high resolution and robustness are commonly at odds. A third important variable affecting this tradeoff is the computational complexity of the solution. A geometric based approach to designing detectors leads to a satisfying compromise: simple to implement detectors that are robust to mismatches and that exhibit good performance. The approach designs a representation subspace that is a good approximation (in the gap metric sense) to the signal set (a priori information), and uses multiresolution and wavelet analysis to design the representation subspace and implement the detector. The approach can be applied to multipath channels, and detection results illustrate the robustness of the geometric gap detector.
{"title":"A geometric and multiresolution analysis approach to robust detection","authors":"José M. F. Moura","doi":"10.1109/SSP.2001.955206","DOIUrl":"https://doi.org/10.1109/SSP.2001.955206","url":null,"abstract":"Summary form only given, as follows. Detection algorithms, whose design takes into account prior knowledge about the signals and the channel, face a quandary: they provide marked improvement in performance when the field operating conditions match well this available knowledge; but they experience strong degradation when the actual conditions depart from the assumed ones. In other words, high resolution and robustness are commonly at odds. A third important variable affecting this tradeoff is the computational complexity of the solution. A geometric based approach to designing detectors leads to a satisfying compromise: simple to implement detectors that are robust to mismatches and that exhibit good performance. The approach designs a representation subspace that is a good approximation (in the gap metric sense) to the signal set (a priori information), and uses multiresolution and wavelet analysis to design the representation subspace and implement the detector. The approach can be applied to multipath channels, and detection results illustrate the robustness of the geometric gap detector.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"48 1","pages":"2-"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76013049","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}
Space-time adaptive processing (STAP) has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe and dynamic interference which generally includes clutter as well as jamming. While the theory of optimum STAP is well known, practical issues, such as interference heterogeneity, finite sample support, mismatched signal models and computational load, need to be overcome when it comes to implementing STAP in operational radar systems. This paper proposes an advanced STAP formulation which addresses important issues facing practical implementation and then tailors this general formulation for the case of interference rejection in over-the-horizon (OTH) radar to evaluate experimentally its target detection and localisation performance.
{"title":"An advanced STAP implementation for surveillance radar systems","authors":"G. Fabrizio, M. Turley","doi":"10.1109/SSP.2001.955240","DOIUrl":"https://doi.org/10.1109/SSP.2001.955240","url":null,"abstract":"Space-time adaptive processing (STAP) has emerged as a key technology for improving the performance of radar systems required to operate in the presence of severe and dynamic interference which generally includes clutter as well as jamming. While the theory of optimum STAP is well known, practical issues, such as interference heterogeneity, finite sample support, mismatched signal models and computational load, need to be overcome when it comes to implementing STAP in operational radar systems. This paper proposes an advanced STAP formulation which addresses important issues facing practical implementation and then tailors this general formulation for the case of interference rejection in over-the-horizon (OTH) radar to evaluate experimentally its target detection and localisation performance.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"10 1","pages":"134-137"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76924030","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 present a method for predicting non-stationary signals generated by a time varying composite source. The method is based on the concept of temporal fuzzy clustering. A fuzzy clustering algorithm is applied to the given part (past+present) of the time series and the calculated clusters and membership matrix are then used to estimate a mixture probability distribution function (PDF) underlying the series. In this way a continuous drift in the series distribution expressed as a drift in the clusters' appearance rate can be estimated. A future PDF can then be predicted by fitting a specific model to the estimated past and future PDF values. This also enables the generation of a minimal-mean-squared-error prediction for a future time series element using the estimated mean value of the predicted PDF.
{"title":"Prediction of time varying composite sources by temporal fuzzy clustering","authors":"S. Policker, A. Geva","doi":"10.1109/SSP.2001.955289","DOIUrl":"https://doi.org/10.1109/SSP.2001.955289","url":null,"abstract":"We present a method for predicting non-stationary signals generated by a time varying composite source. The method is based on the concept of temporal fuzzy clustering. A fuzzy clustering algorithm is applied to the given part (past+present) of the time series and the calculated clusters and membership matrix are then used to estimate a mixture probability distribution function (PDF) underlying the series. In this way a continuous drift in the series distribution expressed as a drift in the clusters' appearance rate can be estimated. A future PDF can then be predicted by fitting a specific model to the estimated past and future PDF values. This also enables the generation of a minimal-mean-squared-error prediction for a future time series element using the estimated mean value of the predicted PDF.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"2 1","pages":"329-332"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88889623","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 demonstrate the use of support vector (SV) techniques for the binary classification of nonstationary sinusoidal signals with quadratic phase. We briefly describe the theory underpinning SV classification, and introduce Cohen's group time-frequency representation, which is used to process the nonstationary signals so as to define the classifier input space. We show that the SV classifier outperforms alternative classification methods on this processed data.
{"title":"Nonstationary signal classification using support vector machines","authors":"Arthur Gretton, Manuel Davy, A. Doucet, P. Rayner","doi":"10.1109/SSP.2001.955283","DOIUrl":"https://doi.org/10.1109/SSP.2001.955283","url":null,"abstract":"We demonstrate the use of support vector (SV) techniques for the binary classification of nonstationary sinusoidal signals with quadratic phase. We briefly describe the theory underpinning SV classification, and introduce Cohen's group time-frequency representation, which is used to process the nonstationary signals so as to define the classifier input space. We show that the SV classifier outperforms alternative classification methods on this processed data.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"128 1","pages":"305-308"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89689913","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 introduces a novel semiblind approach to space-time linear detection in multiple-access systems. A new criterion for the selection of the linear receiver coefficients, based on the maximum likelihood (ML) principle, is derived and a practical implementation by means of a fast expectation-maximization (EM) algorithm is suggested. The semiblind criterion is obtained from a purely statistical point of view where the aim of training data is not to enhance performance but to eliminate misconvergence problems.
{"title":"An application of the maximum likelihood principle to semiblind space-time linear detection in multiple-access wireless communications","authors":"M. Bugallo, J. Míguez, L. Castedo","doi":"10.1109/SSP.2001.955256","DOIUrl":"https://doi.org/10.1109/SSP.2001.955256","url":null,"abstract":"This paper introduces a novel semiblind approach to space-time linear detection in multiple-access systems. A new criterion for the selection of the linear receiver coefficients, based on the maximum likelihood (ML) principle, is derived and a practical implementation by means of a fast expectation-maximization (EM) algorithm is suggested. The semiblind criterion is obtained from a purely statistical point of view where the aim of training data is not to enhance performance but to eliminate misconvergence problems.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"41 1","pages":"198-201"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85149868","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}
B. Karlsen, Jan Larsen, Helge B. D. Sørensen, K. Jakobsen
This paper presents statistical signal processing approaches for clutter reduction in stepped-frequency ground penetrating radar (SF-GPR) data. In particular, we suggest clutter/signal separation techniques based on principal and independent component analysis (PCA/ICA). The approaches are successfully evaluated and compared on a real SF-GPR time-series. Field-test data are acquired using a monostatic S-band rectangular waveguide antenna.
{"title":"Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection","authors":"B. Karlsen, Jan Larsen, Helge B. D. Sørensen, K. Jakobsen","doi":"10.1109/SSP.2001.955243","DOIUrl":"https://doi.org/10.1109/SSP.2001.955243","url":null,"abstract":"This paper presents statistical signal processing approaches for clutter reduction in stepped-frequency ground penetrating radar (SF-GPR) data. In particular, we suggest clutter/signal separation techniques based on principal and independent component analysis (PCA/ICA). The approaches are successfully evaluated and compared on a real SF-GPR time-series. Field-test data are acquired using a monostatic S-band rectangular waveguide antenna.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"33 1","pages":"146-149"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86292727","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 consider the problem of blind equalization of nonlinear channels from the second-order statistics of the channel output. The channel model is linear in the parameters, with additive terms that are nonlinear functions of the transmitted symbols. All previous approaches assume that the corresponding channel matrix has full column rank, which ensures the existence of linear FIR zero forcing equalizers. We show that this assumption is not necessary, and that under certain circumstances linear FIR equalizers can be found despite the violation of this assumption. An important consequence of this fact is that equalization can be effected with a smaller level of diversity. In this paper necessary and sufficient conditions on the channel matrix are given. An algorithm for the computation of the equalizers is also given for those channels satisfying these conditions, assuming an i.i.d. symbol sequence and memory dominance of the linear part.
{"title":"On blind equalization of rank deficient nonlinear channels","authors":"Roberto López-Valcarce, S. Dasgupta","doi":"10.1109/SSP.2001.955274","DOIUrl":"https://doi.org/10.1109/SSP.2001.955274","url":null,"abstract":"We consider the problem of blind equalization of nonlinear channels from the second-order statistics of the channel output. The channel model is linear in the parameters, with additive terms that are nonlinear functions of the transmitted symbols. All previous approaches assume that the corresponding channel matrix has full column rank, which ensures the existence of linear FIR zero forcing equalizers. We show that this assumption is not necessary, and that under certain circumstances linear FIR equalizers can be found despite the violation of this assumption. An important consequence of this fact is that equalization can be effected with a smaller level of diversity. In this paper necessary and sufficient conditions on the channel matrix are given. An algorithm for the computation of the equalizers is also given for those channels satisfying these conditions, assuming an i.i.d. symbol sequence and memory dominance of the linear part.","PeriodicalId":70952,"journal":{"name":"信号处理","volume":"82 1","pages":"269-272"},"PeriodicalIF":0.0,"publicationDate":"2001-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84234693","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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