系统工程与电子技术 ›› 2022, Vol. 44 ›› Issue (8): 2419-2426.doi: 10.12305/j.issn.1001-506X.2022.08.05

• 电子技术 • 上一篇    下一篇

基于自适应免疫算法的欺骗信号检测方法

常浩伟1,*, 庞春雷1, 郭泽辉1, 张良1, 吕敏敏2, 张闯3   

  1. 1. 空军工程大学信息与导航学院, 陕西 西安 710077
    2. 中国人民解放军95801部队, 北京 100893
    3. 中国人民解放军95510部队, 贵州 贵阳 550029
  • 收稿日期:2021-10-25 出版日期:2022-08-01 发布日期:2022-08-24
  • 通讯作者: 常浩伟
  • 作者简介:常浩伟(1998—), 男, 硕士研究生, 主要研究方向为智能导航与协同控制|庞春雷(1986—), 男, 副教授, 博士, 主要研究方向为组合导航、数据处理|郭泽辉(1997—), 男, 硕士研究生, 主要研究方向为组合导航抗欺骗检测|张良(1987—), 男, 副教授, 博士, 主要研究方向为组合导航、数据处理|吕敏敏(1986—), 女, 助理工程师, 硕士, 主要研究方向为军用通信与导航应用|张闯(1992—), 男, 工程师, 博士, 主要研究方向为组合导航和导航对抗技术

Spoofing signal detection method based on adaptive immunity algorithm

Haowei CHANG1,*, Chunlei PANG1, Zehui GUO1, Liang ZAHNG1, Minmin LYU2, Chuang ZHANG3   

  1. 1. Information and Navigation College, Air Force Engineering University, Xi'an 710077, China
    2. Unit 95801 of the PLA, Beijing 100893, China
    3. Unit 95510 of the PLA, Guiyang 550029, China
  • Received:2021-10-25 Online:2022-08-01 Published:2022-08-24
  • Contact: Haowei CHANG

摘要:

针对常见的转发式欺骗干扰, 提出了一种基于自适应免疫算法的欺骗信号检测方法。在载波相位双差检测的基础上, 构造正常信号和欺骗信号两种检测模式; 然后利用免疫算法获取待检测数据与监测器的亲和度指数, 筛选出符合阈值要求的监测器, 从而解算出待检测数据隶属于各检测模式的概率。为进一步解决在实际检测过程中出现的虚警问题, 引入自适应算法对交叉概率和变异概率进行非线性自适应调节, 提高了检测结果的准确性。实验结果表明, 所提方法对于欺骗信号检测准确率能够达到98.8%, 有效地实现了欺骗干扰信号检测。

关键词: 转发式欺骗, 载波相位双差观测值, 免疫算法, 欺骗检测, 自适应算法

Abstract:

Aiming at the problems of complex ambiguity resolution and limited application scenarios in carrier phase difference detection method, an spoofing signal detection method based on adaptive immune algorithm is proposed. Based on the carrier phase double difference detection, two detection modes of normal signal and deception signal are constructed; Then the immune algorithm is used to obtain the affinity index between the data to be detected and the monitor, and the monitors that meet the threshold requirements are selected, so as to calculate the probability that the data to be detected belongs to each detection mode. In order to solve the problem of false alarm in the actual detection process, an adaptive algorithm is introduced to adjust the crossover probability and mutation probability nonlinearly, which improves the accuracy of the detection results. The experimental results show that the accuracy of the proposed method for deception signal detection can reach 98.8%, and the deception interference signal detection is effectively realized.

Key words: forward spoofing, carrier phase double difference observation value, immune algorithm, deception detection, adaptive algorithm

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