Tracking a High Maneuver Target Based on Intelligent Matrix Covariance Resetting

Abstract

A high accurate tracking technique with the use of intelligent approach on matrix covariance resetting is proposed in this paper. In practice, the conventional Kalman filters have a fast convergence rate at the beginning. However, after some iteration the Kalman filter steps become very small. To overcome this defect and to make use of Kalman filter abilities, the matrix covariance resetting idea is used. The matrix covariance presetting usually is used to improve the tracking algorithm result especially for high maneuvering targets. To determine the optimal value of the unknown resetting parameter in each step, the intelligent fuzzy block is used. In this paper, an innovative technique is presented, which resets covariance matrix by using fuzzy logic. It is demonstrated by means of numerical acceleration examples that the tracking capability of the proposed method is essentially as good as that of the traditional methods, especially for high maneuver targets.