Hybrid GNSS-ToA localization and tracking via cooperative unscented Kalman filter

Abstract

Cooperative localization algorithms have been recently introduced to overcome the limitations of systems relying on GPS or other terrestrial infrastructure. The novel hybrid cooperative unscented Kalman filter (hcUKF) approach, which fuses ranging data from both satellites and terrestrial receivers, allows increased availability, robustness and accuracy compared to GNSS-only localization in challenged scenarios. Simulation results show that the proposed solution outperforms traditional algorithms such as extended Kalman filter.