Localization and trajectory estimation of mobile objects with a single sensor

The localization problem in mobile sensors is aimed at identifying the spatial location of an object with reference to a known coordinate system. Existing solutions assume that multiple (generally three or more) sensors around the object know their position and the solution is obtained by using a triangulation scheme. Such solutions are not computationally feasible when the object or sensor are moving. In this paper, we present a novel method to solve the localization problem for an object whose position is unknown using a single moving sensor whose position is known. The proposed method relies on multiple time samples from the moving sensor to estimate the trajectory of the moving object. We derive the Cramer-Rao bound for the localization parameters and use an unscented Kalman filter to estimate the parameters from noisy measurements.