A Multidimensional Scaling Approach for Cooperative GNSS Navigation

A plethora of applications require precise and reliable positioning and navigation, for which Global Navigation Satellite Systems (GNSS) are the main source of information. The main drawback of GNSS is their degraded performance in harsh environments. A possible way to overcome such limitation is to resort to cooperative positioning (CP) strategies, where a set of receivers share information to improve their position estimates. In this contribution we propose a CP GNSS method, relying on Multidimensional Scaling (MDS), to cope with the main limitation of standard CP solutions: allow for a subset of receivers to be in GNSS-denied conditions. The main parameters impacting the overall system performance are discussed, and the performance of the GNSS-MDS approach compared to standalone and cooperative GNSS state-of-the art techniques.