Improving iterated Extended Kalman Filter for non-Gaussian noise environments
L Kam-Kim, H Dang-Ngoc… - Proceedings of 2011 6th …, 2011 - ieeexplore.ieee.org
Proceedings of 2011 6th International Forum on Strategic Technology, 2011•ieeexplore.ieee.org
Kalman filter is an efficient algorithm to estimate the state of linear time-discrete dynamical
systems with Gaussian noises. Unfortunately, practical systems are mostly non-linear and
noise follows non-Gaussian distributions. This article proposes an improvement in Extended
Kalman Filter (EKF) algorithm for predicting non-Gaussian distributed state noise. Further
introducing the proposed scheme into the indoor positioning system illustrates that
considerably higher accuracy in locating and tracking objects can be achieved.
systems with Gaussian noises. Unfortunately, practical systems are mostly non-linear and
noise follows non-Gaussian distributions. This article proposes an improvement in Extended
Kalman Filter (EKF) algorithm for predicting non-Gaussian distributed state noise. Further
introducing the proposed scheme into the indoor positioning system illustrates that
considerably higher accuracy in locating and tracking objects can be achieved.
Kalman filter is an efficient algorithm to estimate the state of linear time-discrete dynamical systems with Gaussian noises. Unfortunately, practical systems are mostly non-linear and noise follows non-Gaussian distributions. This article proposes an improvement in Extended Kalman Filter (EKF) algorithm for predicting non-Gaussian distributed state noise. Further introducing the proposed scheme into the indoor positioning system illustrates that considerably higher accuracy in locating and tracking objects can be achieved.
ieeexplore.ieee.org
以上显示的是最相近的搜索结果。 查看全部搜索结果