Locating a target from directional data

Statistical estimation plays an important role in locating a target in space, a task that has important applications in many areas. However, theoretical measures on the quality of various estimators reported in the literature have been difficult to obtain because of mathematical complications. As a result, choice of estimator in practice has been largely arbitrary. In this paper, we present a systematic study on major target estimators reported in the literature. Focus is on comparisons between the traditional angle method, the line method, and a recently developed line-to-point transformation method. Insights gained from the study directly lead to the development of a novel two-stage angle method that not only produces highly accurate target estimation among all known estimators but is also computationally efficient.