Nonlinear Gaussian mixture PHD filter with an H_∞ criterion

This paper is devoted to the problem of multitarget tracking with nonlinear models and uncertain noise statistics in the framework of random finite sets. Based on the linear approximation strategy, a robust closed-form solution to the probability hypothesis density recursion is proposed in terms of an H∞ norm minimization criterion. This idea is extended to develop another analytic implementation using the unscented transform technique. Simulations using the proposed approach are also presented.