Signal Tracking Based on Kalman Filtering

The objective of tracking filtering is to accurately estimate target states from acquired observation data, with the key challenge being the ability to track maneuvering targets. The primary difficulty in maneuvering target tracking lies in the mismatch between predefined target models and actual target dynamics models. The Kalman filter implementation typically involves state prediction and measurement update cycles, where system matrices define motion models and measurement matrices relate states to observations.