Abstract
We present a non-linear, probabilistic prediction model developed and implemented to track spatial location and other navigation characteristics of a barge traveling on the inland waterway system. A pre-filter, to check the validity of the measurements, a non-linear speed estimation process, and a Kalman filter to predict the navigation solution of the barge is developed in this work. Due to the complex dynamics involved in the system, a non-linear stochastic model was developed in state space using system dynamics to represent the process and measurement systems while maintaining the fidelity of an actual system. The algorithm was verified using actual measurements obtained from multiple barges on multiple rivers acquired from different sensors. The results show a reliable and robust prediction algorithm for tracking inland waterway barges.