On the High-SNR Conditional Maximum-Likelihood Estimator Full Statistical Characterization
Alexandre Renaux, Philippe Forster, Éric Chaumette, Pascal Larzabal · IEEE Transactions on Signal Processing · 2006
In the field of asymptotic performance characterization of the conditional maximum-likelihood (CML) estimator, asymptotic generally refers to either the number of samples or the signal-to-noise ratio (SNR) value. The first case has been already fully characterized, although the second case has been only partially investigated. Therefore, this correspondence aims to provide a sound proof of a result, i.e., asymptotic (in SNR) Gaussianity and efficiency of the CML estimator in the multiple parameters case, generally regarded as trivial but not so far demonstrated