Nonlinear target tracking algorithm based on block ensemble Kalman filter

As target tracking performance depends on correlated tracks and the selection of filter initial states, ensemble Kalman filter was introduced to nonlinear target tracking system, and the feasibility and validity of the system were verified. A new target tracking algorithm based on block ensemble Kalman filter was proposed, where initial ensemble was produced by the block method, and covariance matrix weighting was used for all the blocks in the target tracking process. The simulation results show that the algorithm based on block ensemble Kalman filter has the same computational complexity as previous ensemble Kalman filter while offers higher estimation accuracy for motion parameters, and can fulfill real-time tracking in contrast to high computational complexity of particle filter.