WSN-based passenger localization in severe NLOS environments using SDP

In this work we use wireless sensor networks (WSNs) to estimate positions for automated passenger registration with the purpose of an electronic ticketing application in public transport systems. The network is capable of measuring distances between the network's sensor nodes by phase-of-arrival (POA) ranging. In our application, the requirements regarding position accuracy are very demanding, due to the ranging biases caused by severe non-line-of-sight (NLOS) environments, i.e. highly reflective radio propagation. Hence, we suggest semidefinite programming (SDP) as a robust optimization algorithm for the localization process and apply a NLOS mitigation technique from literature to a modified cost function that may help to meet these requirements. Finally the proposed algorithm is compared with state-of-the-art positioning techniques. Testing with simulated and real measured data shows that the proposed SDP estimator outperforms the other positioning algorithms substantially, particularly in realistic NLOS environments.