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We consider problems of wireless sensor network (WSN) - based localisation as a promising technology for highly accurate positioning solutions. Hence, this paper provides an overview on the results of synthetic data testing of an iterative positioning approach. Position estimation in WSNs is based on distance measuring by means of time-of-flight (TOF) ranging techniques. To employ radio frequency (RF) - based positioning here an iterative classical multidimensional scaling (C-MDS) approach is used for computing position estimates by applying the eigen-decomposition of an Eucledian kernel. The iterative process enables coping with not RF connected sensor nodes. Based on various simulations, we investigate this approach in terms of performance and especially convergence speed.