Hierarchical underwater localization in dominating background flow fields

The effect of ocean flow on the motion of autonomous underwater vehicles (AUV) is often crucial in the development of underwater localization algorithms and should not be treated as small disturbances. The domination of strong ocean currents and the requirement of low power consumption prohibit AUVs to move against a background flow to obtain localization correction in a timely manner. Our recent studies, among others, enable an unmanned vehicle to follow a near optimal trajectory found by Lagrangian coherent structures based fluid control algorithm with minimal fuel usage, which improves the vehicles' runtime and the path following accuracy in the presence of strong background flow. Here, we propose a three-dimensional fully distributed localization hierarchy to improve the localization of low-cost mobile marine data collection underwater sensor networks using intra-vehicle communication and measurements. The proposed algorithm is realized by using the extended Kalman filter. Correlation terms in covariance matrices are considered independently to meet the distributed feature. Resulting simulated localization errors are bounded at satisfactory levels and the relationship between the number of AUVs and the performance of the algorithm is investigated.