The Application of CI-CSCKF Fusion in Tracking the Mid-Course of Boost-Glide Vehicles

In recent years, boost-glide vehicles have been widely studied in the military field of various powers. Because boost-glide vehicles can still generate maneuverability and high maneuverability in the free-glide segment, the traditional dynamic model-based tracking method is no longer applicable in this field. Due to the multisensor fusion tracking effect is superior to the single sensor tracking, combined with the field of maneuvering target tracking commonly used “current” statistical model, and compared with the UKF, nonlinear filter such as CKF filter has better stability and smaller computation. CS-CKF tracking model was constructed, and through the two radar observations, using the theory of Covariance Intersection (CI) fusion of two groups of observation data integration CI-CSCKF fusion. Simulation results show that the estimation effect of CI-CSCKF fusion algorithm is better than the tracking effect of single sensor based on CSCKF.