A New Nonlinear Filter Method for Ballistic Target Tracking

Abstract:

In order to track the ballistic re-entry target, a new kind of ballistic target tracking algorithm, square-root quadrature Kalman filter (SRQKF) algorithm, was proposed. The proposed algorithm is the square-root implementation of the quadrature Kalman filter (QKF). The quadrature Kalman filter is a recursive, nonlinear filtering algorithm developed in the Kalman filtering framework and computes the mean and covariance of all conditional densities using the Gauss-Hermite quadrature rule. The square-root quadrature Kalman filter propagates the mean and the square root of the covariance. It guarantees the symmetry and positive semi-definiteness of the covariance matrix, improved numerical stability and the numerical accuracy, but at the expense of increased computational complexity slightly.

• Periodical: Applied Mechanics and Materials (Volumes 135-136)
• Pages: 99-105
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.135-136.99
• Online since: October 2011
• Authors: Chun Ling Wu, Yong Feng Ju
• Keywords: Ballistic Target Tracking, Gauss-Hermite Quadrature, Quadrature Kalman Filter, Re-Entry

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