Analysis of database referenced navigation by the combination of heterogeneous geophysical data and algorithms

In this study, an EKF (Extended Kalman Filter) based database reference navigation using both gravity gradient and terrain data was performed to complement the weakness of using only one type of geophysical DB (Database). Furthermore, a new algorithm which combines the EKF and profile matching was developed to improve the stability and accuracy of the positioning. On the basis of simulations, it was found that the overall navigation performance was improved by the combination of geophysical DBs except the two trajectories in which the divergence of TRN (Terrain Referenced Navigation) occurred. To solve the divergence problem, the profile matching algorithm using the terrain data is combined with the EKF. The results show that all trajectories generate the stable performance with positioning error ranges between 14m to 23m although not all trajectories positioning accuracy is improved. The average positioning error from the combined algorithm for all nine trajectories is about 18 m. For further study, a development of a switching geophysical DB or algorithm between the EKF and the profile matching to improve the navigation performance is suggested.