Litcius/Paper detail

It<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si23.svg"><mml:mover accent="true"><mml:mi mathvariant="normal">o</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:math>-Taylor-based square-root unscented Kalman filtering methods for state estimation in nonlinear continuous-discrete stochastic systems

Gennady Yu. Kulikov, Maria V. Kulikova

2020European Journal of Control24 citationsDOIOpen Access PDF

Topics & Concepts

Cholesky decompositionKalman filterCovarianceSquare rootAlgorithmComputer scienceApplied mathematicsMathematicsStatisticsEigenvalues and eigenvectorsArtificial intelligencePhysicsQuantum mechanicsGeometryTarget Tracking and Data Fusion in Sensor NetworksInertial Sensor and NavigationStructural Health Monitoring Techniques
It<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si23.svg"><mml:mover accent="true"><mml:mi mathvariant="normal">o</mml:mi><mml:mo>^</mml:mo></mml:mover></mml:math>-Taylor-based square-root unscented Kalman filtering methods for state estimation in nonlinear continuous-discrete stochastic systems | Litcius