Deadbeat Source Localization from Range-only Measurements: a Robust Kernel-based Approach

In this paper, a novel non-asymptotic method for target localization based on the algebra of Volterra linear integral operators is presented aiming at estimating the coordinate of a stationary source by a single mobile agent. The algorithm assumes that the agent is only allowed to obtain the measurement of distance from the source. By properly designing the kernel of the Volterra operators, the influence of initial conditions on the transient phase can be eliminated in order to achieve – ideally – a deadbeat mode of behavior. The stability analysis shows that the algorithm is robust to bounded additive measurement perturbations. Moreover, the bias on the estimate due to time-discretization is characterized. Simulation results show that the proposed algorithm is characterized by fast convergence and good noise immunity.