FGPF-BLUE Tracking for Maneuvering Reentry Targets
Zhao Yu-qin · Electronics Optics & Control · 2011
The tracking problems of maneuvering reentry targets often turn out to be highly nonlinear problems,for both of the dynamic and the observation models could be nonlinear.In order to overcome the disadvantages of Extended Kalman Filter(EKF) and Particle Filter(PF) in precision and real-time performance,a new nonlinear filter was proposed.The new FGPF-BLUE(Fast Gaussian Particle Filter-Best Linear Unbiased Estimator) filter was constructed by combining predictive steps of the FGPF and the updating steps of the BLUE and was,therefore,a semi-Monte Carlo method.The dynamic model of a maneuvering reentry target was established and was processed by EKF,PF and FGPF-BLUE filter.The comparison of those filters shows that the new filter has a higher steady-state precision than others and consumes less time than PF.