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A Strong Interference Suppressor for Satellite Signals in GNSS Receivers

机译:GNSS接收机中强大的卫星信号干扰抑制器

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摘要

In this paper, we discuss a method to protect satellite signals from strong time-varying interferers. Time-domain, transform-domain, and space-domain algorithms have been widely used for interference suppression. However, when used under high dynamic conditions, these methods cause serious suppression of satellite signals in the GPS receivers along with inhibiting interferers. To address this problem, we optimize the satellite and interference steering vectors using a multi-star forming approach to distinguish satellite signals and strong interferers. In order to detect time-varying interferers, we further introduce a novel hidden Markov model (HMM), and power inversion (PI) and Multi-star interference suppressed (Multi-PI) model anti-interference synthesis scheme.A bank of HMM filters are operated to track the on-off interferers in the frequency domain, and decide if an anti-interference algorithm needs to be used. After HMM, the Multi-PI algorithm is implemented to inhibit broadband interferers. The experimental results show that our novel scheme adapts quickly when tracking time-varying interferers and protects GPS signals from losses.
机译:在本文中,我们讨论了一种保护卫星信号免受强烈时变干扰的方法。时域,变换域和空间域算法已被广泛用于干扰抑制。但是,在高动态条件下使用时,这些方法会严重抑制GPS接收器中的卫星信号并抑制干扰源。为了解决这个问题,我们使用多星形成方法来优化卫星和干扰控制矢量,以区分卫星信号和强干扰源。为了检测时变干扰源,我们进一步介绍了一种新颖的隐马尔可夫模型(HMM),功率倒置(PI)和多星干扰抑制(Multi-PI)模型抗干扰综合方案。运算符在频域中跟踪开/关干扰源,并确定是否需要使用抗干扰算法。在HMM之后,实施Multi-PI算法以抑制宽带干扰。实验结果表明,我们的新方案可以在跟踪时变干扰源时快速适应,并保护GPS信号免受损失。

著录项

  • 来源
    《Circuits, systems, and signal processing》 |2017年第7期|3004-3019|共16页
  • 作者单位

    Fujian Univ Technol, Sch Informat Sci & Engn, Fuzhou 350108, Fujian, Peoples R China|Wuhan Univ, Elect & Informat Sch, Wuhan 430072, Hubei, Peoples R China;

    Fujian Univ Technol, Sch Informat Sci & Engn, Fuzhou 350108, Fujian, Peoples R China|Wuhan Univ, Elect & Informat Sch, Wuhan 430072, Hubei, Peoples R China;

    Wuhan Univ, Elect & Informat Sch, Wuhan 430072, Hubei, Peoples R China;

    Wuhan Univ, Elect & Informat Sch, Wuhan 430072, Hubei, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hidden Markov model (HMM); Multi-PI algorithm; Time-varying; Anti-interference;

    机译:隐马尔可夫模型(HMM);多PI算法;时变;抗干扰;

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