Some Relations Between Extended and Unscented Kalman Filters

By Fredrik K. Gustafsson, Gustaf Hendeby. IEEE Transactions on Signal Processing, 2012

367 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/afebd74e6c5f2e3b03c1fadfabf122e8c68b5544

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. Lamine Mili
2. Marcos Netto
3. Junbo Zhao

In Artificial Intelligence

1. Marcos Netto
2. Junbo Zhao
3. Lamine Mili
4. C. Karlgaard

Citations in the corpus

• A Robust Iterated Extended Kalman Filter for Power System Dynamic State Estimation (2017, methodology): “Specifically, the IEKF linearizes the system nonlinear equations iteratively to compensate for the higherorder terms, whereas the UKF leverages the unscented transformation by deterministically providing sigma points to approximate the mean and covariance matrix of a random state vector, thus achiev”