Was ist der Kalman Filter?

Was ist der Kalman Filter?

Der Kalman Filter findet einen Schätzer eines dynamischen Systems anhand von vorhe- rigen Messungen und einem Systemmodell, welches das zu messende System simuliert. Der Kalman Filter benutzt die Information, welche ihm das vorherige Zeitintervall liefert, um eine a-priori Vorhersage zu treffen.

Wie wird das Kalman Filter auch genannt?

Das Kalman-Filter (auch Kalman-Bucy-Filter, Stratonovich-Kalman-Bucy-Filter oder Kalman-Bucy-Stratonovich-Filter) ist ein mathematisches Verfahren zur iterativen Schätzung von Parametern zur Beschreibung von Systemzuständen auf der Basis von fehlerbehafteten Beobachtungen.

What is Kalman filter and how it works?

Kalman Filter can have similar results as the Particle filter with right tuning, model selection and outliers detection/rejection mechanism. Anomalies on measurements can be solved by using an approach such as the Mahalanobis distance. Moreover, we will focus on its implementation rather than deriving the whole Kalman Filter.

Does a Kalman filter assume that the errors are Gaussian?

Using a Kalman filter does not assume that the errors are Gaussian. However, the filter yields the exact conditional probability estimate in the special case that all errors are Gaussian.

What is the difference between the Dempster-Shafer theory and the Kalman filter?

In the Dempster–Shafer theory, each state equation or observation is considered a special case of a linear belief function and the Kalman filter is a special case of combining linear belief functions on a join-tree or Markov tree.

What is the Kalman gain equation of HP + R1?

HP + R 1 (11.27) Equation 11.27 is the Kalman gain equation. The inno v ation, i k de ned in eqn. 11.17 has an asso ciated measuremen t prediction co v ariance. HP + R 1 = P 0 k K k HP = ( I K k H ) P 0 (11.29) Equation 11.29 is the up date equation for error co v ariance matrix with optimal gain.