Ocean Current-Aided Localization and Navigation for Underwater Gliders with Information Matching Algorithm

The underwater glider (UG) is a new type of long-endurance marine vehicle that is currently widely used in marine environment surveillance. However, the limited capability of underwater communication and the uncertainty of the marine environment leads to a large deviation between the dead-reckoned trajectory and the real trajectory of UG. Therefore, a localization and navigation method based on ocean current data is proposed in this study. Firstly, the working principle and configuration of UG are illustrated, and the dynamic model is also analyzed. Then, the depth-averaged current is derived with motion parameters of UG, and the ocean current data from the Hybrid Coordinate Ocean Model is also introduced and processed. Meanwhile, to make an accurate localization, the DAC is stratified according to the layer weight extracted from the processed ocean current model to obtain layered DAC (LDAC). Subsequently, because the sample intervals of sensors are asynchronous with LDAC, a new matching algorithm based on sample time difference is presented to match the information of sensors and LDAC. Furthermore, the matched data is applied to localization for accurate dead reckoning. Finally, based on the data collected from two experiments, the LDAC-aided localization method proposed in this paper is compared with other benchmark positioning methods, including dynamic model-aided localization, sea current-aided localization, and acoustic beacon-aided localization methods. The results indicate that the proposed new method achieves better localization performance than other benchmark methods. In addition, the proposed method could be applied to other autonomous vehicles with communication constraints.