Estimation of trajectories of pipeline PIGs using inertial measurements and non linear sensor fusion

This paper presents a nonlinear sensor fusion algorithm for inertial navigation designed to reconstruct trajectories of a Pipeline Inspection Gauge. Outputs of a strapdown inertial measurement unit are combined with non inertial measurements provided by an incremental odometer and a set of cartographic landmarks. The navigation system is modeled as a nonlinear dynamic system and the extended Kalman filter is used to estimate the system state. On preliminary experiments, it was possible to reconstruct a closed test trajectory with 2,800 m of extension, attaining a final error of 1.7 m.