Collaborative High Accuracy Localization in Mobile Multipath Environments
The authors study the problem of high accuracy localization of mobile nodes in a multipath-rich environment where sub-meter accuracies are required. They employ a peer-to-peer framework where the vehicles/nodes can get pair-wise multipath-degraded ranging estimates in local neighborhoods together with a fixed number of anchor nodes. The challenge is to overcome the multipath-barrier with redundancy in order to provide the desired accuracies especially under severe multipath conditions when the fraction of received signals corrupted by multipath is dominating. They invoke a analytical graphical model framework based on particle filtering and reveal its high accuracy localization promise through simulations.