Fig 4. Illustration of localization toy problems.

(A) The sensors and objects locations on a sphere are marked by green stars and dots, respectively. The multi-sensor observations correspond to Simulation 1 (left), Simulation 2 (middle), and Simulation 3 (right). (B) Results of the application of our approach to Simulation 1: the SSDs obtained by the proposed method (left), the diffusion maps embedding (middle), and the localization confusion matrix obtained by a 10-fold cross-validation with an RBF SVM classifier (right). (C) A comparison between the localization accuracy obtained by the proposed method based on SSDs and the localization accuracy obtained based on the output of each sensor as well as the concatenation of the output from all the sensors. The localization accuracy is the number of correctly identified positions divided by the true number of total positions in each region.