Current field tracking based on spatiotemporal evolution model with distributed networked underwater sensor system

Abstract

Distributed networked underwater sensor (DNUS) system can provide ocean measurements over a wide area with a large number of sensors. This paper studies the estimation of the two-dimensional ocean current field with acoustic travel time difference data observed by a DNUS system. Considering that the current field is correlated in time and space, we present a statistical-based tomography method based on Kalman filter to reconstruct and track the ocean current field. A spatiotemporal autoregressive (AR) model is used to describe the evolution of the current field. In the spatiotemporal AR model, the observation region is divided into sub-triangle grids. The sub-triangles are partitioned into clusters by distance and each cluster is assigned with one AR coefficient. The AR coefficients are updated adaptively with the past estimated current velocities. The proposed method is verified with the synthetic observational data generated by a barotropic ocean model and the tomography experiment conducted near Zhoush...