System state estimation in the presence of noise is critical for control systems, signal processing, and many other applications in a variety of fields. Develop

Kalman filtering seems quite simple in concept, requires no command of, or special skills in abstract mathematics, and has been discussed in abundance during th

System state estimation in the presence of noise is critical for control systems, signal processing, and many other applications in a variety of fields. Develop

Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the err