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Communication Dans Un Congrès Année : 2008

MULTICHANNEL AR PARAMETER ESTIMATION FROM NOISY OBSERVATIONS AS AN ERRORS-IN-VARIABLES ISSUE

Patrick Roussilhe
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Résumé

In various applications from radar processing to mobile communication systems based on CDMA or OFDM, M-AR multichannel processes are often considered and may be combined with Kalman filtering. However, the estimations of the M-AR parameter matrices and the covariance matrices of the additive noise and the driving process from noisy ob-servations is a key issue to be addressed. In this paper, we propose to solve this problem as an errors-in-variables problem. Thus, the noisy observation autocorrelation matrix compensated by a specific diagonal block matrix and whose kernel is defined by the M-AR parameters matrices must be positive semi-definite. Hence, the parameter estimation con-sists in searching every diagonal block matrix that satisfies this property, in reiterating this search for a higher model order and then in extracting the solution that belongs to both sets. The proposed algorithm outperforms existing methods, especially for low Signal-to-Noise Ratio and when the variances of the additive noise are not necessarily the same on each channel
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Dates et versions

hal-00349758 , version 1 (04-01-2009)

Identifiants

  • HAL Id : hal-00349758 , version 1

Citer

Julien Petitjean, Eric Grivel, William Bobillet, Patrick Roussilhe. MULTICHANNEL AR PARAMETER ESTIMATION FROM NOISY OBSERVATIONS AS AN ERRORS-IN-VARIABLES ISSUE. eusipco 2008, Aug 2008, lausanne, Switzerland. pp. ⟨hal-00349758⟩
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