simultaneous estimation of the range and the angle of close emitters usually requires a multidimensional search. this paper proposes analgorithm to improve the position of an element for arrays designed on the basis of some certain or random rules. in the proposed method,one element moves along the same previous direction, maintaining its vertical distance from each source, to reach a constella...

The Cramér-Rao bound (CRB), a well-known lower on the performance of any unbiased parameter estimator, has been used to study wide variety problems. However, obtain CRB, requires an analytical expression for likelihood measurements given parameters, or equivalently precise and explicit statistical model data. In many applications, such is not available. Instead, this work introduces novel appro...

In most situations the best estimator of a function of the parameter exists, but sometimes it has a complex form and we cannot compute its variance explicitly. Therefore, a lower bound for the variance of an estimator is one of the fundamentals in the estimation theory, because it gives us an idea about the accuracy of an estimator. It is well-known in statistical inference that the Cram&eac...

As an application of the improved Cauchy-Schwartz inequality due to Walker (Statist. Probab. Lett. (2017) 122:86-90), we obtain an improved version of the Cramer-Rao inequality for randomly censored data derived by Abdushukurov and Kim (J. Soviet. Math. (1987) pp. 2171-2185). We derive a lower bound of Bhattacharya type for the mean square error of a parametric function based on randomly censor...

The Cramer-Rao Lower Bound is widely used in statistical signal processing as a benchmark to evaluate unbiased estimators. However, for some random variables, the probability density function has no closed analytical form. Therefore, it is very hard or impossible to evaluate the Cramer-Rao Lower Bound directly. In these cases the characteristic function may still have a closed and even simple f...