系统工程与电子技术 ›› 2026, Vol. 48 ›› Issue (8): 2638-2647.doi: 10.12305/j.issn.1001-506X.2026.08.12

• 传感器与信号处理 • 上一篇    

基于航迹残差的弹道导弹目标识别技术

孙军1(), 秦琨1,2(), 方明1(), 薛俊杰1(), 于守江1,2()   

  1. 1. 上海航天电子通讯设备研究所,上海 201109
    2. 西安电子科技大学电子工程学院,陕西 西安 710071
  • 收稿日期:2025-04-24 修回日期:2025-06-14 接受日期:2025-07-01 出版日期:2026-03-06 发布日期:2026-03-06
  • 通讯作者: 方明 E-mail:sj15222968357@163.com;35415505@qq.com;zj02065119@163.com;2576102591@qq.com;18121077076@163.com
  • 作者简介:孙 军(2001—),男,硕士研究生,主要研究方向为雷达信号处理
    秦 琨(1982—),男,研究员,硕士,主要研究方向为雷达总体设计
    薛俊杰(1988—),男,高级工程师,硕士,研究方向为雷达数据处理
    于守江(1984—),男,研究员,硕士,研究方向为雷达系统设计
  • 基金资助:
    钱学森青年创新基金;上海航天青博计划资助课题

Ballistic missile target recognition technology based on track residuals

Jun SUN1(), Kun QIN1,2(), Ming FANG1(), Junjie XUE1(), Shoujiang YU1,2()   

  1. 1. Shanghai Aerospace Electronic Technology Institute,Shanghai 201109,China
    2. School of Electronic Engineering,Xidian University,Xi’an 710071,China
  • Received:2025-04-24 Revised:2025-06-14 Accepted:2025-07-01 Online:2026-03-06 Published:2026-03-06
  • Contact: Ming FANG E-mail:sj15222968357@163.com;35415505@qq.com;zj02065119@163.com;2576102591@qq.com;18121077076@163.com

摘要:

针对弹道导弹目标识别方法易受诱饵特性干扰,且单次判决结果波动大、实时性不足等问题,提出一种基于航迹残差的弹道导弹目标识别技术。首先对弹道目标进行运动学建模,并仿真得到雷达回波信号;接着对回波信号进行恒虚警率处理、凝聚处理和滤波跟踪处理,并提取航迹残差特征;最后对残差特征进行阈值单次判决,并采用滑窗投票法进行时序序贯融合,从而实现目标识别。实验结果表明,该方法能够有效区分弹头与诱饵簇,且针对残差特征的识别处理方法比较稳健并具有良好的准确率和实时性。本研究为弹道导弹防御系统提供了思路。

关键词: 弹道导弹, 目标识别, 航迹残差, 滑窗投票法

Abstract:

To address the issues of ballistic missile target recognition methods being susceptible to interference from decoy characteristics, as well as significant fluctuations in single decision results and insufficient real-time performance, a ballistic missile target recognition technology based on trajectory residuals is proposed. Firstly, a kinematic model is established for ballistic targets, and radar echo signals are simulated. Subsequently, the echo signals undergo constant false alarm rate processing, clustering processing, filtering tracking processing, and trajectory residual features are extracted. Finally, threshold single decision is performed on the residual features, and a sliding window voting method is adopted for temporal sequential fusion, thereby achieving target recognition. Experimental results demonstrate that this method can effectively distinguish between warheads and decoy clusters, and the recognition processing method for residual features is relatively robust, with good accuracy and real-time performance. This study provides insights for ballistic missile defense systems.

Key words: ballistic missile, target recognition, track residual, sliding window voting

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