High-Order Filtering of LIDAR Data to Assist Coal Shiploading
A high-order signal model is proposed in which the states are Kronecker tensor products of probability distributions. This model enables an optimal linear filter to be specified. A minimum residual error variance criterion may be used to select the number of discretizations and Kronecker products. The filtering of LIDAR data from a coal shiploader environment is investigated. It is demonstrated that the proposed method can outperform conventional Kalman and hidden Markov model filters.
IEEE Transactions on Aerospace and Electronic Systems
Interdisciplinary Engineering not elsewhere classified