View in EDS

A trajectory tracking algorithm of ballistic missile in the ascent phase with unknown noise statistical characteristics.

Saved in:
Bibliographic Details
Title: A trajectory tracking algorithm of ballistic missile in the ascent phase with unknown noise statistical characteristics.
Authors: Liu, Lili1 (AUTHOR) lllzhy0426@163.com, Mu, Rongjun1 (AUTHOR) murjun@hit.edu.cn, Cui, Naigang1 (AUTHOR)
Source: Mechanical Systems & Signal Processing. Jul2025, Vol. 235, pN.PAG-N.PAG. 1p.
Subjects: Tracking algorithms, Kernel functions, Phase noise, Ballistic missiles, Random noise theory
Abstract: • The improved three-dimensional gravity turning (GT3) model is proposed. • Unify the dimensions of GT3 and dynamic models in the IMM of the ascent phase. • Integrate variational Bayesian framework based on Cauchy kernel function (VC) into GT3-based CKF-IMM (VCCKF-GIMM). • The adaptive robust filtering algorithm based on improved variational iteration cut-off time is proposed. • The VCCKF-GIMM algorithm identify the burn-out point and the noise mutation point. In this study, a trajectory tracking algorithm of ballistic missile in the ascent phase with unknown noise statistical characteristics is proposed. Firstly, the three-dimensional gravity turning (GT3) model is integrated into the interactive multi-model (IMM) algorithm, and an asymmetric IMM algorithm based on dimension unity is obtained. On this basis, integrate variational Bayesian framework based on Cauchy kernel function (VC) into the GT3-IMM algorithm based on Cubature Kalman filter (VCCKF-GIMM), and the adaptive robust filtering algorithm based on improved variational iteration cut-off time is proposed. Finally, the simulation verification is carried out under a variety of simulation conditions. The simulation results show this study realizes the high-precision continuous tracking, which can detect the burn-out point in Gaussian noise and the noise mutation point of time-varying noise. The accuracy of ballistic estimation and the robustness of the system have been significantly improved, under unknown noise statistical characteristics. [ABSTRACT FROM AUTHOR]
Copyright of Mechanical Systems & Signal Processing is the property of Academic Press Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Description
Abstract:• The improved three-dimensional gravity turning (GT3) model is proposed. • Unify the dimensions of GT3 and dynamic models in the IMM of the ascent phase. • Integrate variational Bayesian framework based on Cauchy kernel function (VC) into GT3-based CKF-IMM (VCCKF-GIMM). • The adaptive robust filtering algorithm based on improved variational iteration cut-off time is proposed. • The VCCKF-GIMM algorithm identify the burn-out point and the noise mutation point. In this study, a trajectory tracking algorithm of ballistic missile in the ascent phase with unknown noise statistical characteristics is proposed. Firstly, the three-dimensional gravity turning (GT3) model is integrated into the interactive multi-model (IMM) algorithm, and an asymmetric IMM algorithm based on dimension unity is obtained. On this basis, integrate variational Bayesian framework based on Cauchy kernel function (VC) into the GT3-IMM algorithm based on Cubature Kalman filter (VCCKF-GIMM), and the adaptive robust filtering algorithm based on improved variational iteration cut-off time is proposed. Finally, the simulation verification is carried out under a variety of simulation conditions. The simulation results show this study realizes the high-precision continuous tracking, which can detect the burn-out point in Gaussian noise and the noise mutation point of time-varying noise. The accuracy of ballistic estimation and the robustness of the system have been significantly improved, under unknown noise statistical characteristics. [ABSTRACT FROM AUTHOR]
ISSN:08883270
DOI:10.1016/j.ymssp.2025.112952