Tracking and data association
Kalman filtering: theory and practice
Kalman filtering: theory and practice
| Hi-index | 0.00 |
This paper proposes three exponentially correlated acceleration approaches for accuracy and computational complexity. These models are Singer model, Bar-Shalom and Fortmann's model. Simulation results show that the Singer models and the Bar-Shalom and Fortmann models, each a six state estimate model, require approximately the same number of flops. The Bar-Shalom and Fortmann model requires more flops due to the size of the Q and G matrices. The Sklansky model is a four state estimator and requires about 2/3 of the number of flops of the Singer model.