Dynamic Ship Positioning Using the Time-Frequency Distributions and Kalman Filtering

Today, oil drilling is mainly done in deep waters far from the coastal area. In addition, for purpose of easier maintenance and transportation, drilling rigs usually float on water. However, transport vessels cannot be anchored under such conditions, so they need a dynamic positioning technique to keep the stationary position relative to a reference point on the sea surface. Dynamic positioning systems provide the ability to control ship position and direction using a combination of thruster mechanism and propulsion, measurements of essential vessel variables, as well as the surrounding impacts, such as wind speed. The required criteria for performing a given task, as well as the surrounding conditions and expectations of behaviors at different natural phenomena, together have an impact on designing dynamic positioning systems. Accuracy of the observed dynamic positioning system depends on the selected wave filtering method and controller design. In order to reduce the amount of thruster oscillations, it is necessary to filter noisy signal measurements in terms of their reconstruction and subsequent use for the purpose of control. Some advanced filtering techniques utilize the Kalman recursive filter, which provides optimum estimated values from the noisy measurements by minimizing the error variation for linear and nonlinear signals. Another approach to noise removal is based on time-frequency distributions. For this purpose, high-resolution, reduced interferences time-frequency distributions should be developed and used. Adaptive, datadriven filtering in the time-frequency domain may be used to enhance accuracy of the positioning systems and mathematical models of the vessel, as well as the characteristics of the waves that appear to be a disturbance when performing a task on water.