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检索条件"任意字段=2008 IEEE Sensor Array and Multichannel Signal Processing Workshop"

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multichannel system identification methods for sensor array calibration in uncertain multipath environments

Multichannel system identification methods for sensor array ...

引用

11th ieee workshop on Statistical signal processing (SSP 2001)

作者： Varadarajan, V Krolik, JL Duke Univ Dept Elect & Comp Engn Durham NC 27708 USA

ISBN: (纸本)0780370112

This paper concerns the problem of estimating the array element relative gain and phase responses using sources of opportunity in an uncertain multipath environment. Unlike previous methods, which assume uncorrelated source wavefronts, we propose to perform calibration in a correlated multipath environment. We present two algorithms that apply traditional blind, single input multiple output (SIMO) methods to the array calibration problem. Calibration is performed by discriminating the received components which remain the same for all sources and are thus due to the receiver gains and phases. Simulation results demonstrate the effectiveness of both techniques in terms of reduced sidelobe levels.

关键词： Communication channels (information theory)

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Proceedings of the 2000 ieee sensor array and multichannel signal processing workshop. SAM 2000 (Cat. No.00EX410)

Proceedings of the 2000 IEEE Sensor Array and Multichannel S...

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sensor array and multichannel signal processing workshop

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multichannel system identification methods for sensor array calibration in uncertain multipath environments

Multichannel system identification methods for sensor array ...

引用

ieee/SP workshop on Statistical signal processing (SSP)

作者： V. Yaradarajan J.L. Krolik Dept. of Electr. & Comput. Eng. Duke Univ. Durham NC USA Department of Electrical and Computer Engineering Duke University Durham NC USA

This paper concerns the problem of estimating the array element relative gain and phase responses using sources of opportunity in an uncertain multipath environment. Unlike previous methods, which assume uncorrelated source wavefronts, we propose performing calibration in a correlated multipath environment. We present two algorithms that apply traditional blind, single-input multiple-output (SIMO) methods to the array calibration problem. Calibration is performed by discriminating the received components which remain the same for all sources and are thus due to the receiver gains and phases. Simulation results demonstrate the effectiveness of both techniques in terms of reduced sidelobe levels.

关键词： sensor arrays System identification sensor systems Calibration Phased arrays Performance gain Azimuth Least squares approximation Least squares methods Phase estimation

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multichannel detection and spatial signature estimation with uncalibrated receivers

Multichannel detection and spatial signature estimation with...

引用

ieee/SP workshop on Statistical signal processing (SSP)

作者： A. Leshem A.-J. van der Veen Department Electrical Engineering/DIMES Delft University of Technnology Delft Netherlands

A problem occurring in radio astronomy is the detection and cancellation of spatially correlated interfering signals entering via the sidelobes of the telescopes in an array. A complicating factor is that the noise powers can be different at each telescope. For the case that the sensors are uncalibrated, we formulate the detection problem as a test on the covariance structure, state the GLRT for this problem, and relate it to a simpler ad-hoc detector. We derive algorithms to estimate the noise powers and the subspace of interferer signature vectors. Once the subspace is estimated, the interference can be projected out. We compare this method to the conventional multichannel subspace detector and show its robustness to non-identical channels on data collected with the Westerbork radio telescope.

关键词： sensor arrays Interference Covariance matrix Detectors Telescopes Receivers Radio astronomy Testing Additive noise Radar detection

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The properties of adaptive algorithms with time varying weights

The properties of adaptive algorithms with time varying weig...

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Zatman, M MIT Lincoln Lab Lexington MA 02420 USA

ISBN: (纸本)0780363396

Most adaptive array processing schemes assume that the interference is 'wide sense stationary'. However, in practice this assumption is often violated. For example there may be motion of either the array and/or the interference during the processing interval. The asymptotic performance of two adaptive beamforming algorithms which compensate for this type of changing interference scenario are analyzed in this paper.

关键词： Adaptive algorithm Adaptive arrays Algorithm design and analysis array signal processing Covariance matrix Interference Laboratories Performance analysis signal to noise ratio Vectors

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Improved array self calibration with large sensor position errors for closely spaced sources

Improved array self calibration with large sensor position e...

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Flanagan, BP Bell, KL Mitre Corp Reston VA 20190 USA

ISBN: (纸本)0780363396

Self-calibration algorithms estimate both source directions-of-arrival (DOAs) and perturbed array response vector parameters, such as sensor locations. Calibration errors are usually assumed to be small and a first order approximation to the perturbed array response vector is often used to simplify the estimation procedure. ln this paper, we improve on a previously presented technique that eliminates the small error assumption. The improved technique has better performance for closely spaced sources for both small and large calibration errors.

关键词： array signal processing Calibration Covariance matrix Direction of arrival estimation Matrix decomposition Multiple signal classification Mutual coupling Phased arrays sensor arrays sensor phenomena and characterization

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Tracking time-varying mixing system in blind separation

Tracking time-varying mixing system in blind separation

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Enescu, M Koivunen, V Helsinki Univ Technol Signal Proc Lab FIN-02015 Helsinki Finland

ISBN: (纸本)0780363396

This paper addresses the problem of blind separation from time varying noisy mixtures. The goal is to adapt to changes that occur in the mixing system as well as to estimate if the number of sources change over time. This is achieved by using an adaptive predictor corrector structure and subspace tracker. Changes in the array covariance matrix are used in revealing changes in the mixing system. The performance of the algorithm is studied in simulations.

关键词： Additive noise Blind source separation Covariance matrix Filters sensor arrays signal processing signal processing algorithms Source separation Speech enhancement Time varying systems

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Nonparametric statistics for DOA estimation in the presence of multipath

Nonparametric statistics for DOA estimation in the presence ...

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Visuri, S Oja, H Koivunen, V Helsinki Univ Technol Signal Proc Lab FIN-02015 Helsinki Finland

ISBN: (纸本)0780363396

This paper is concerned with array signal processing in non-Gaussian 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.

关键词： array signal processing Covariance matrix Direction of arrival estimation Gaussian noise Maximum likelihood estimation Noise robustness signal processing algorithms signal resolution Spatial resolution Statistics

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Optimum subband filterbank design for radar array signal processing with pulse compression

Optimum subband filterbank design for radar array signal pro...

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Rabinkin, D Nguyen, T MIT Lincoln Lab Lexington MA 02173 USA

ISBN: (纸本)0780363396

A front-end radar array processing system that operates in the subband domain is considered. It is assumed that pulse compression will be performed on radar return signals in the subband domain. A cohesive algorithm is presented that optimizes the design of all filters used in the subbanding process. These include the analysis filter (used to decompose return signals into narrowband components), the synthesis filter (used when combining subband components after processing), and the pulse compression generating filter (used to generate subband pulse compression filters from a wideband pulse compression filter). The algorithm attempts to minimize system aliasing noise, frequency distortion, and subband processing operations count.

关键词： Algorithm design and analysis array signal processing Design optimization Filter bank Pulse compression methods Pulse generation Radar signal processing signal design signal generators signal processing algorithms

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Local polynomial approximation based beamforming for localization of rapidly moving sources

Local polynomial approximation based beamforming for localiz...

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1st ieee sensor array and multichannel signal processing workshop (SAM 2000)

作者： Katkovnik, V Gershman, AB Tampere Univ Technol Int Ctr Signal Proc FIN-33101 Tampere Finland

ISBN: (纸本)0780363396

A windowed local polynomial approximation (LPA) of time-varying directions-of-arrival (DOA's) is exploited to derive a new form of beamformer for source localization and tracking in highly nonstationary environments. The relationship between our LPA-beamformer and the conventional beamformer is derived. Closed-form expressions are obtained for the bias and variance of the LPA-beamformer in the non stationary case and the problem of optimal window choice is discussed.

关键词： array signal processing Closed-form solution Direction of arrival estimation Gaussian noise Motion estimation Polynomials sensor arrays signal processing signal processing algorithms Tracking

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