Fundamentals of Kalman Filtering: A Practical Approach

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Performance Enhancement of MEMS-Based INS/GPS Integration for Low-Cost Navigation Applications (2009, methodology): “The well-known KF equations [7]–[11], [46] can now be applied to these linearized system models to obtain an optimal filter for state estimation xk based on the measurements up to zk.”
Noise-induced schooling of fish (2019, methodology): “Finally, using a Kalman filter approach [45] we tracked individuals, allowing us to obtain their velocities.”
A comparison of unscented and extended Kalman filtering for estimating quaternion motion (2003, methodology): “The process model we use is an orientatiotdangular velocity (OV) model defined by where q is the current quatemion and w is a pure vector quaternion representing angular velocity.”
Equivalence and Differences Between Structural Equation Modeling and State-Space Modeling Techniques (2010, methodology): “…models is a set of estimation algorithms collectively known as the KF—an online estimation procedure used to predict current or future states (e.g., factor scores) given information up to the current time point by minimizing prediction errors in the least squares sense (Zarchan & Musoff, 2000).”