This article treats integration of navigation data from a variety of sensors in a submarine using extended Kalman filtering in order to improve the accuracy of position, velocity and heading estimates. The problem has been restricted to planar motion. The measurement system consists of an inertial navigation system, a gyro compass, a passive log, an active log and a satellite navigation system. These subsystems are briefly described and models for the measurement errors are given.

Four different extended Kalman filters have been tested by computer simulations. The simulations distinctly show that the passive subsystems alone are insufficient to improve the estimate of the position obtained from the inertial navigation system. A log measuring the velocity relative to the ground or a position determining system are needed. The improvement depends on the accuracy of the measuring instruments, the extent of time the instrument can be used and which filter is being used. The most complex filter, which contains fourteen states, eight to describe the motion of the submarine and six to describe the measurement system, including a model of the inertial navigation system, works very well.