center for robotics and embedded systems University of Southern California Viterbi School of Engineering


In this note, we illustrate the effect of nonlinear state propagation in the unscented Kalman Filter (UKF). We consider a simple nonlinear system, consisting of a two-axis inertial measurement unit. Our intent is to show that the propagation of a set of sigma points through a nonlinear process model in the UKF can produce a counterintuitive (but correct) updated state estimate. We compare the results from the UKF with those from the well-known extended Kalman Filter (EKF), to highlight how the UKF and the EKF differ.


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