Collisions and groundings at sea still occur, and can result in financial loss, loss of life, and damage to the environment. Due to the size and capacity of moden vessels, damage can be extensive. Statistics indicate that the primary cause of accidents at sea is human error, which is often attributed to misinterpretation of the information presented to the mariner. Until recently, data collected from sensors about the vessel were displayed on the bridge individually, leaving the mariner to assimilate the material, make decisions and alter the vessels controls as appropriate. With the advent of the microprocessor a small amount of integration has taken place, but not to the extent that it has in other industries, for example the aerospace industry. This thesis presents a practical method of integrating all the navigation sensors. Through the use of Kalman filtering, an estimate of the state of the vessel is obtained using all the data available. Previous research in this field has not been implemented due to the complexity of the ship modelling process required, this is overcome by incorporating a system identification proceedure into the filter. The system further reduces the demands on the mariner by applying optimal control theory to guide the vessel on a predetermined track. Hazards such as other vessels are not incorporated into this work but they are specified in further research. Further development work is also required to reduce computation time.