What is the Kalman Filter used for in navigation?

Master the Navigation, Seamanship, and Shiphandling (NSS) – Officer of the Deck (OOD) Phase 2 Exam with engaging flashcards and multiple choice questions, complete with hints and explanations. Prepare comprehensively for your test!

At its heart, the Kalman Filter is an optimal estimator that combines a motion model with noisy sensor measurements to produce the best possible estimate of the vessel’s state. In navigation, the inertial navigation system provides position and velocity estimates from accelerometers and gyroscopes, but those readings drift over time due to biases and noise. The filter predicts the next state using the motion model, then uses actual sensor data or external measurements (such as GPS or other fix sources) to correct that prediction. The result is a continuously updated state with quantified uncertainty, reducing drift and improving accuracy as more measurements come in. It shines when fusing data from sensors with different noise characteristics, delivering a robust real-time navigation estimate. It isn’t used for weather forecasting, fuel calculations, or emergency maneuvers; its role is to refine the navigation state by filtering and integrating diverse observations.