An implementation of Unscented Kalman Filter for nonlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded for unlinear state estimation. However, it may cause significant error for highly nonlinear systems because of The propagation of uncertainty through The unlinear system. The Unscented Kalman Filter (UKF) is a will development in The field. The idea is to produce several from points (Sigma points) around The current state estimate -based on its covariance. Then, propagating these points through The nonlinear map to get more accurate estimation of The mean and covariance of The mapping results. In this way, it avoids The need to calculate The Jacobian, hence incurs only The similar computation load as The EKF. For tutorial purpose, this code implements a simplified version of UKF, where we assume both the process and measurement are additive to avoid augment of state and a

license.txt
ukf.m

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．