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In this paper, we exploit the maximum correntropy criterion (MCC) torobustify the traditional time-difference-of-arrival (TDOA) location estimatorin the presence of non-line-of-sight (NLOS) propagation conditions. For thesake of statistical efficiency, the correntropy-based robust loss is imposed onthe underlying time-of-arrival composition via joint estimation of the sourceposition and onset time, instead of the TDOA counterpart generated in thepostprocessing of sensor-collected timestamps. We then employ a neurodynamicoptimization approach to tackle the highly nonconvex MCC formulation.Furthermore, we examine the local stability of equilibrium for thecorresponding projection-type neural network model. Simulation investigationsin representative NLOS propagation scenarios demonstrate that our neurodynamicrobust TDOA localization solution is capable of outperforming several existingschemes in terms of positioning accuracy.

Neurodynamic TDOA localization with NLOS mitigation via maximum correntropy criterion