Transcription of Unscented Kalman Filter Tutorial
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Unscented Kalman Filter TutorialGabriel A. TerejanuDepartment of Computer Science and EngineeringUniversity at Buffalo, Buffalo, NY IntroductionThe Unscented Kalman Filter belongs to a bigger class of filters calledSigma-Point Kalman FiltersorLinear Regression Kalman Filters, which are using thestatistical linearizationtechnique[1,5]. This technique is used to linearize a nonlinear function of a random variable through a linearregression betweennpoints drawn from the prior distribution of the random variable. Since we areconsidering the spread of the random variable the techniquetends to be more accurate than Taylorseries linearization [7].
q n 1−W0 P k−1 i is the row or column of the matrix square root of n 1−W0 P k−1. W 0 controls the position of sigma points: W0 ≥ 0 points tend to move further from the origin, W0 ≤ 0 points tend to be closer to the origin. A more general selection scheme for sigma points, called scaled unscented transformation, is given in [9, 2 ...
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