Modeling error sensitivity of the MUSIC algorithm conditioned on resolved sources
Paper in proceeding, 2008

When the correlation matrix is known, the resolution power of subspace algorithms is infinite. In the presence of modelling errors, even if the correlation matrix is known, sources can no longer be resolved with certainty. Focusing on the MUSIC algorithm [1], the purpose of this work is to provide closed form expression of bias and variance versus the model mismatch (these errors can be different for each source). Un-like previous work, these performance measures are derived conditioned on the success of a certain source resolution test. Among the resolution definitions proposed in [2], we investigate which one is more suitable for our purposes. Numerical results support the theoretical investigations. Our findings are of a great interest for the determination of the necessary antenna calibration accuracy to achieve specifications on the estimator performance.

Author

A. Ferreol

Laboratoire des Systemes et Applications des Technologies de l'Information et de l'Energie

Thales Group

P. Larzabal

Laboratoire des Systemes et Applications des Technologies de l'Information et de l'Energie

Mats Viberg

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

European Signal Processing Conference

22195491 (ISSN)

Subject Categories

Signal Processing

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Latest update

3/25/2020