[Legacy Report] State Estimation and Target Tracking using the Kalman Filter

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It can be challenging to estimate the state of a dynamic system, as required, for example, to track a maneuvering underwater target. The Kalman filter is often at the core of target tracking systems, but many other components are required for an effective and reliable tracking system. This requirement is especially important in scenarios where there can be multiple, disparate sensors and multiple targets in significant noise.

In this presentation, Dr. Garfield Mellema will describe the construction of target tracking systems and the role that each of the major components plays in the operation of an effective system. The discussion will centre around improvements to enhance its capabilities and performance. Some tracking results will be shown.

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