Analysis of the Cramer-Rao Bound Integrating a Prior-Knowledge

Abstract : Introducing prior-knowledge of some damped/undamped poles in the estimation of the parameters of a mutli-poles sinusoidal model is an important problem as for instance in bearing estimation or in biomedical signal analysis. The principle is to orthogonally project the data onto the noise space associated with the known poles. As the Cramér-Rao Lower Bound (CRB) gives a benchmark against which algorithms performance can be compared, it is useful to derive the CRB associated with this model, named Prior-CRB (P-CRB). In particular, we analyze this bound in the context of close subspaces context, ie., when the known poles are close to the unknown ones.
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Communication dans un congrès
2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP 2007, Dec 2007, Virgin Islands, United States. IEEE, pp.25-28, 〈10.1109/CAMSAP.2007.4497956〉
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https://hal-supelec.archives-ouvertes.fr/hal-01247033
Contributeur : Remy Boyer <>
Soumis le : lundi 21 décembre 2015 - 05:36:11
Dernière modification le : jeudi 5 avril 2018 - 12:30:05

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Remy Boyer. Analysis of the Cramer-Rao Bound Integrating a Prior-Knowledge. 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMPSAP 2007, Dec 2007, Virgin Islands, United States. IEEE, pp.25-28, 〈10.1109/CAMSAP.2007.4497956〉. 〈hal-01247033〉

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