Applying the unscented Kalman filter for nonlinear state estimation

By Rambabu Kandepu, Bjarne A. Foss, Lars Struen Imsland. 2008

557 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/a70f980717d79d93703345f3eee5004f00056c5c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Luis A. Aguirre
2. Dennis S. Bernstein
3. Leonardo A. B. Tôrres
4. Bruno Otávio Soares Teixeira

In Artificial Intelligence

1. Luis A. Aguirre
2. Dennis S. Bernstein
3. Leonardo A. B. Tôrres
4. Bruno Otávio Soares Teixeira

In Control and Systems Engineering

1. Luis A. Aguirre
2. Dennis S. Bernstein
3. Leonardo A. B. Tôrres
4. Bruno Otávio Soares Teixeira
5. Wilfrid Perruquetti
6. Wassim M. Haddad
7. Andrey E. Polyakov
8. Zhihong Man

Citations in the corpus

• On unscented Kalman filtering with state interval constraints (2010, methodology): “Model information is used during the forecast step, while measurement data are injected into the estimates during the data-assimilation step.”