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Mathematical Problems in Engineering
Volume 2016, Article ID 3921608, 11 pages
http://dx.doi.org/10.1155/2016/3921608
Research Article

Tracking Air-to-Air Missile Using Proportional Navigation Model with Genetic Algorithm Particle Filter

Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi’an 710038, China

Received 17 November 2015; Accepted 25 February 2016

Academic Editor: Vladimir Turetsky

Copyright © 2016 Hongqiang Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The purpose of this paper is to track the air-to-air missile. Here we put forward the PN-GAPF (Proportional Navigation motion model and Genetic Algorithm Particle Filter) method to solve the problem. The main jobs we have done can be listed as follows: firstly, we establish the missile state space model named as the Proportional Navigation (PN) motion model to simulate the real motion of the air-to-air missile; secondly, the PN-EKF and PN-PF methods are proposed to track the missile, through combining PN motion model with EKF and PF; thirdly, in order to solve the particle degeneracy and diversity loss, we introduce the intercross and variation in GA to the particles resampling step and then the PN-GAPF method is put forward. The simulation results show that the PN motion model is better than the CV and CA motion models for tracking the air-to-air missile and that the PN-GAPF method is more efficient than the PN-EKF and PN-PF.