Distributed estimation for range difference tracking without noise statistical characteristic

This article is concerned with the distributed target tracking problem with range-only measurement, where the statistical characteristics of the system noises are unknown. First, the nonlinear measurement equation is transformed into a linear model using a type of nonlinear transformation, which can avoid the linearization errors caused by the Taylor expansion and unscented transform. The noise statistical characteristic of the converted measurement noise is still unknown, but it can be derived as bounded noise. Then, by minimizing the upper bound of estimation error, the spectral radius inequalities are constructed to determine the optimal estimator gain sequence. Meanwhile, the stability determination is derived during the estimator design. Finally, a target tracking example is presented to show the effectiveness of the proposed method.