0000000000296926

AUTHOR

Samuli Visuri

showing 4 related works from this author

Nonparametric statistics for DOA estimation in the presence of multipath

2002

This paper is concerned with array signal processing in nonGaussian noise and in the presence of multipath. Robust and fully nonparametric high resolution algorithms for direction of arrival (DOA) estimation are presented. The algorithms are based on multivariate spatial sign and rank concepts. Spatial smoothing of the multivariate rank and sign based covariance matrices is employed as a preprocessing step in order to deal with coherent sources. The performance of the algorithms is studied using simulations. The results show that almost optimal performance is obtained in wide variety of different noise conditions.

Signal processingRank (linear algebra)business.industryNoise (signal processing)Nonparametric statisticsDirection of arrivalPattern recognitionArtificial intelligenceCovariancebusinessSmoothingMultipath propagationMathematicsProceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop. SAM 2000 (Cat. No.00EX410)
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Robust subspace DOA estimation for wireless communications

2002

This paper is concerned with array signal processing in non-Gaussian noise typical in urban and indoor radio channels. Robust and fully nonparametric high resolution algorithms for direction of arrival (DOA) estimation are presented. The algorithms are based on multivariate spatial sign and rank concepts. The performance of the algorithms is studied using simulations. The results show that almost optimal performance is obtained in wide variety of noise conditions.

Signal processingbusiness.industryNoise (signal processing)Covariance matrixElectronic engineeringNonparametric statisticsWirelessDirection of arrivalbusinessAlgorithmSubspace topologyMathematicsMatrix decompositionVTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026)
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Affine equivariant multivariate rank methods

2003

The classical multivariate statistical methods (MANOVA, principal component analysis, multivariate multiple regression, canonical correlation, factor analysis, etc.) assume that the data come from a multivariate normal distribution and the derivations are based on the sample covariance matrix. The conventional sample covariance matrix and consequently the standard multivariate techniques based on it are, however, highly sensitive to outlying observations. In the paper a new, more robust and highly efficient, approach based on an affine equivariant rank covariance matrix is proposed and outlined. Affine equivariant multivariate rank concept is based on the multivariate Oja (Statist. Probab. …

Statistics and ProbabilityPure mathematicsApplied MathematicsMatrix t-distributionMultivariate normal distributionNormal-Wishart distributionCombinatoricsEstimation of covariance matricesScatter matrixStatistics::MethodologyMatrix normal distributionMultivariate t-distributionStatistics Probability and UncertaintyMathematicsMultivariate stable distributionJournal of Statistical Planning and Inference
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Sign and rank covariance matrices

2000

The robust estimation of multivariate location and shape is one of the most challenging problems in statistics and crucial in many application areas. The objective is to find highly efficient, robust, computable and affine equivariant location and covariance matrix estimates. In this paper, three different concepts of multivariate sign and rank are considered and their ability to carry information about the geometry of the underlying distribution (or data cloud) are discussed. New techniques for robust covariance matrix estimation based on different sign and rank concepts are proposed and algorithms for computing them outlined. In addition, new tools for evaluating the qualitative and quant…

Statistics and ProbabilityCovariance functionCovariance matrixApplied MathematicsMathematicsofComputing_NUMERICALANALYSISCovariance intersectionCovarianceEstimation of covariance matricesMatérn covariance functionScatter matrixStatisticsRational quadratic covariance functionStatistics Probability and UncertaintyAlgorithmMathematicsJournal of Statistical Planning and Inference
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