基于斜率最优点的三维空间GNSS分布式压制干扰方法

刘志衡; 刘伟平; 焦博

doi:10.12382/bgxb.2025.0095

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基于斜率最优点的三维空间GNSS分布式压制干扰方法

更新时间：2026-04-24

- 基于斜率最优点的三维空间GNSS分布式压制干扰方法
- 3D Space GNSS Distribute Suppression Jamming Method Based on Slope Optimal Point
- 兵工学报 2026年47卷第1期页码：250095
- 作者机构：
  
  网络空间部队信息工程大学地理空间信息学院，河南郑州 450001
- 作者简介：
  
  *通信作者邮箱：lwpchxy@sina.com
- 基金信息：
  
  国家自然科学基金项目(41804035)
- DOI：10.12382/bgxb.2025.0095
  中图分类号： TN972+.1;TN967.1
- 收稿：2025-02-17，
  
  网络首发：2026-02-11，
  
  纸质出版：2026-01-31
- 稿件说明：
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刘志衡, 刘伟平, 焦博. 基于斜率最优点的三维空间GNSS分布式压制干扰方法[J]. 兵工学报, 2026,47(1):250095.

LIU Zhiheng, LIU Weiping, JIAO Bo. 3D Space GNSS Distribute Suppression Jamming Method Based on Slope Optimal Point[J]. Acta Armamentarii, 2026, 47(1): 250095.
刘志衡, 刘伟平, 焦博. 基于斜率最优点的三维空间GNSS分布式压制干扰方法[J]. 兵工学报, 2026,47(1):250095. DOI： 10.12382/bgxb.2025.0095.

LIU Zhiheng, LIU Weiping, JIAO Bo. 3D Space GNSS Distribute Suppression Jamming Method Based on Slope Optimal Point[J]. Acta Armamentarii, 2026, 47(1): 250095. DOI： 10.12382/bgxb.2025.0095.

摘要

为应对无人机蜂群袭扰等问题，可利用多台全球导航卫星系统（Global Navigation Satellite System

GNSS）压制干扰源进行分布式导航压制干扰，在此应用场景下，与地面目标干扰不同，如何开展三维空间GNSS分布式压制干扰，成为新的待解决难题。对现有的基于参考面可视域分析方法进行改进，通过离散化三维空间完成了三维空间的可视域分析，提出一种基于斜率最优点的干扰源部署算法，与现有的基于局部最优点的干扰源部署算法相比，新方法通过斜率能够更加精确地评定待部署点的优劣。实验结果表明：在保持干扰源数量不变的条件下，与全局搜索算法相比，斜率最优算法干扰覆盖率基本保持不变，计算时间能够减少65.93%～86.54%；与局部最优算法相比，斜率最优算法无需提前确定局部最优点等级，可在保证覆盖率的同时降低计算复杂度。

Abstract

In order to deal with the attack by UAV swarm

the multiple global navigation satellite system (GNSS) suppression jamming sources can be used for distributed navigation suppression jamming. In this application scenario

unlike ground target jamming

how to carry out GNSS distributed suppression jamming in 3D space has become a new problem to be solved. Therefore

the existing viewshed analysis method based on reference plane is improved

and the viewshed analysis of 3D space is completed by discretizing 3D space. An jamming source deployment algorithm based on a slope optimal point is proposed. It can more accurately assess the advantages and disadvantages of the points to be deployed by the slope compared with the existing jamming source deployment algorithm based on the local optimal point. Experiments show that

compared with the global search algorithm

the slope optimal algorithm maintains basically the same jamming coverage and reduces the calculation time by 65. 93%-86. 54% under the condition of keeping the number of jamming sources unchanged. Compared with the local optimal algorithm

the slope optimal algorithm does not need to pre-determine the level of local optimal points

and can reduce the computational complexity while ensuring coverage.

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Keywords

references

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