A Direct Method to Generate Approximations of the Barankin Bound

Abstract

The search for an easily computable but tight approximation of the Barankin bound (BB) is important for the prediction of the signal-to-noise ratio (SNR) value where the Cramer-Rao bound (CRB) becomes unreliable for prediction of maximum likelihood estimators (MLE) variance. In this paper we propose a method for the derivation of a general class of BB approximations which has the advantage of a clear interpretation. This method suggests a new practical BB approximation, whose computational complexity does not exceed that of the CRB but which seems tighter than existing approximations