Applications of error intensity measures to bearing estimation

In this paper we will discuss a new class of performance approximations for maximum likelihood type bearing estimation systems. This class is based on the application of various point process models to a sequence of error prone points along the likelihood trajectory. The point process model is described by two quantities: the intensity function of the local maxima locations over the parameter space, and a selection rule for the global maximum from the set of local maxima. This class gives new estimators to the Mean-Square Error and specializes to the approximation techniques of [1] and [6].