Fundamentals of Kalman Filtering: A Practical Approach, Second Edition

Estimation of Roll Damping Coefficient from Roll and Trajectory Data Using Extended Kalman Filter

“…To apply Extended Kalman Filter (EKF) the set of non-linear differential equations representing the system must be expressed in a state space form as [11] ẋ=f(x)+w (13) where vector x represents the state of the system, f(x) is a nonlinear function of the state variables and w is a random, zero mean process noise. Presence of process noise indicates that model of real system is not precise.…”

“…Neural Kalman filter approach to target tracking is presented as a technique to improve the motion model of the target while it is being tracked in flight [10]. EKF is successfully used to estimate ballistics coefficient [11], drag coefficient [12][13] and atmospheric conditions [14] from trajectory data. Flight state parameters of guided projectile are obtained using Extended Kalman filter (EKF) and Linearized Kalman filter (LKF) [15].…”

An Effective Fuel-Level Data Cleaning and Repairing Method for Vehicle Monitor Platform

“…The threshold of detecting fuel consumption is known, and the situation of appearing continuous-time abnormal fuel level is not considered in this method. Some filtering method like Kalman filter, fast Fourier transform (FFT) and discrete wavelet transform (DWT) [13]have been widely used in denoising and outlier detection on sensor data. DWT has been developed rapidly in recent decades and has obvious advantage on temporal resolution [14].…”

Real-time Kalman filter: Cooling of an optically levitated nanoparticle

“…As described in references [77][78][79] we can use the following transformation from linear time invariant system theory (LTI System theory) in order to calculate the continuous-time state transition matrix F(t) for a time-invariant systems dynamics matrix A,…”