  This paper considers the fusion of multiple estimates of a spatially extended
object, where the object extent is modeled as an ellipse parameterized by the
orientation and semiaxes lengths. For this purpose, we propose a novel
systematic approach that employs a distance measure for ellipses, i.e., the
Gaussian Wasserstein distance, as a cost function. We derive an explicit
approximate expression for the Minimum Mean Gaussian Wasserstein distance
(MMGW) estimate. Based on the concept of a MMGW estimator, we develop efficient
methods for the fusion of extended target estimates. The proposed fusion
methods are evaluated in a simulated experiment and the benefits of the novel
methods are discussed.
