On the Accuracy and Resolvability of Vector Parameter Estimates

Chengfang Ren, Mohammed Nabil El Korso, Jerome Galy, Eric Chaumette, Pascal Larzabal, Alexandre Renaux
2014 IEEE Transactions on Signal Processing  
In this paper we address the problem of fundamental limitations on resolution in deterministic parameters estimation. We introduce a definition of resolvability based on probability and incorporating a requirement for accuracy unlike most existing definitions. Indeed in many application the key problem is to obtain distributions of estimates that are not only distinguishable but also accurate and compliant with a required precision. We exemplify the proposed definition with estimators that
more » ... stimators that produce normal estimates, as in the conditional model for which the Gaussianity and efficiency of maximum likelihood estimators (MLEs) in the asymptotic region of operation (in terms of signal-to-noise ratio and/or in large number of snapshots) is well established, even for a single snapshot. In order to measure the convergence in distribution, we derive a simple test allowing to check whether the conditional MLEs operate in the purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org Chengfang Ren is with Universite Paris-Sud/LSS 3, Rue Joliot-Curie,
doi:10.1109/tsp.2014.2328322 fatcat:wbkc2aiyuvdzzhncar4m5dvbum