Estimating the Purse Seine Net Geometry during a Hauling Operation Using a Data Assimilation Method

Abstract

The dynamics of fishing nets can be estimated by modeling and numerically computing the forces acting on them. However, the dynamic models of fishing nets are highly nonlinear owing to the significant influence of hydrodynamic forces acting on the net. Therefore, if there are unknown parameters that define the state of motion in the model, it is often difficult to achieve high accuracy in the numerical simulations of fishing gear and evaluate its dynamics. To address this issue, a method is proposed for estimating these unknown parameters by integrating a nonlinear Kalman filter into a fishing net dynamics model. This study aimed to estimate the hauling velocity of large- and medium-sized purse seine fishing nets, which can be a challenging parameter to measure. The calculations are based on the data obtained from a research operation conducted by the Marine Fisheries Research and Development Center in 2019 using the purse seine fishing vessel “Taikei Maru No. 1”. The time series of the hauling-net velocity was estimated based on the results of the estimation experiment. These results allowed the estimation of the hauling velocity and calculation of the net dynamics during the hauling process. This shows that net dynamics simulation is possible even with unknown parameters.