An Application of Firefly Hybrid Extended Kalman Filter Tracking a Reentry Object

Several mathematical models are used for tracking reentry objects in case of radar and sonar. Bayes law evaluations by Unseen Markov Mannequin is one of these which can be used with compatible Kalman filters. To reduce linearization errors, in metaheurestic methods, a new algorithm is proposed by combination of stochastic and metheuristic techniques. For determination of estimation performance, Firefly Hybrid Extended Kalman Filter has been suggested. Convergence of such systems of firefly is quite high. These are compatible with nonlinear multimodal issues. Simulations studies have been done by MATLAB. The drag resistance is found to be related not only to speed but also to maximum cross sectional errors. The minimization of errors of altitude, velocity and ballistic coefficients are taken to be random. In comparison with Extended Kalman Filter and Hybrid Extended Kalman Filter, the results show 30 to 50 percent error reduction. Combinations of metaheurestic and stochastic methods have immense possibility of development of optimization in case of tracking of reentry objects.