系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (5): 1682-1694.doi: 10.12305/j.issn.1001-506X.2026.05.24

• 制导、导航与控制 • 上一篇    下一篇

基于DMD模态特征提取重构的再入滑翔目标轨迹解析预测

夏文杰1, 张子剑2, 闫循良1,*   

  1. 1. 西北工业大学航天学院,陕西 西安 710072
    2. 北京宇航系统工程研究所,北京 100076
  • 收稿日期:2025-03-24 出版日期:2026-05-27 发布日期:2026-05-27
  • 通讯作者: 闫循良
  • 作者简介:夏文杰(2001—),男,博士研究生,主要研究方向为飞行器弹道设计与制导、目标轨迹预测
    张子剑(1987—),男,高级工程师,博士,主要研究方向为飞行器设计

Analytical trajectory prediction for entry gliding targets based on extraction and reconstruction of DMD modes

Wenjie XIA1, Zijian ZHANG2, Xunliang YAN1,*   

  1. 1. School of Astronautics,Northwestern Polytechnical University,Xi’an 710072,China
    2. Beijing Institute of Astronautical Systems Engineering,Beijing 100076,China
  • Received:2025-03-24 Online:2026-05-27 Published:2026-05-27
  • Contact: Xunliang YAN

摘要:

针对传统目标轨迹预测算法多任务适用性和实时性不足的问题,提出一种基于交互式多模型跟踪和动力学模态分解(dynamic model decomposition, DMD)的再入滑翔目标轨迹解析预测方法。首先,构建基于Singer模型的再入滑翔目标跟踪模型,通过交互式多模型跟踪算法实现对目标运动的快速估计,为后续的特征提取环节提供必要的目标数据支撑。随后,基于混叠数据序列的模态分解思想,设计一种基于高阶DMD(high-order DMD, HODMD)的模态特征提取方法,可通过分析目标的多维实时跟踪数据实现对目标DMD模态特征的提取。最终,按照模态振幅大小筛选主导动力学模态,并将其重构得到具有简单代数求和形式的目标轨迹解析表达式,进而实现对目标未来轨迹的快速解析预测。以美国高超声速通用航空飞行器为对象的目标轨迹预测仿真结果表明,所提方法可在目标动力学模型未知的情况下,实现对目标轨迹的高精度解析预测,且相比于基于控制变量估计的轨迹预测方法,所提方法具有较高的轨迹预测精度和计算效率优势。

关键词: 临近空间再入滑翔目标, 轨迹解析预测, 交互式多模型, 特征提取, 动力学模态分解

Abstract:

To address the limitations of traditional target trajectory prediction algorithms in multi-task adaptability and real-time performance, an analytical trajectory prediction method for entry gliding targets based on interactive multiple model tracking and dynamical mode decomposition (DMD) is proposed. Firstly, Singer model-based tracking model is established for entry gliding targets, enabling rapid estimation of target motion through interactive multiple model tracking algorithms. This provides essential target data support for subsequent feature extraction steps. Subsequently, inspired by the mode decomposition idea of mixed data sequences, a mode feature extraction method based on high-order DMD (HODMD) is designed. By analyzing multi-dimensional real-time tracking data of the target, this method extracts DMD mode features of target. Finally, dominant dynamical modes are selected based on the magnitude of mode amplitudes, and the target’s trajectory is reconstructed into an analytical expression with simple algebraic summation form. This enables fast analytical prediction of the target’s future trajectory. Simulation results of target trajectory prediction for the common aero vehicle-hypersonic? (CAV-H) demonstrate that the proposed method achieves high-precision analytical prediction of the target trajectory even when the target’s dynamical model is unknown. Compared to control variable estimation-based trajectory prediction methods, the proposed method offers superior trajectory prediction accuracy and computational efficiency advantages.

Key words: near-space re-entry gliding target, analytical trajectory prediction, interactive multiple model (IMM), feature extraction, dynamical mode decomposition (DMD)

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