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Huber 稳健回归在 GNSS 干扰抑制中的应用。

Huber's Non-Linearity for GNSS Interference Mitigation .

机构信息

European Commission, Joint Research Centre (JRC) Directorate for Space, Security and Migration; Via Enrico Fermi 2749, 21027 Ispra (VA), Italy.

Northeastern University, Electrical and Computer Engineering Department, 360 Huntington Ave, Boston, MA 02115, USA.

出版信息

Sensors (Basel). 2018 Jul 10;18(7):2217. doi: 10.3390/s18072217.

Abstract

Satellite-based navigation is prevalent in both commercial applications and critical infrastructures, providing precise position and time referencing. As a consequence, interference to such systems can have repercussions on a plethora of fields. Additionally, Privacy Preserving Devices (PPD)—jamming devices—are relatively inexpensive and easy to obtain, potentially denying the service in a wide geographical area. Current jamming mitigation technology is based on interference cancellation approaches, requiring the detection and estimation of the interference waveform. Recently, the Robust Interference Mitigation (RIM) framework was proposed, which leverages results in robust statistics by treating the jamming signal as an outlier. It has the advantage of rejecting jamming signals without detecting or estimating its waveform. In this paper, we extend the framework to situations where the jammer is sparse in some transformed domain other than the time domain. Additionally, we analyse the use of Huber’s non-linearity within RIM and derive its loss of efficiency. We compare its performance to state-of-the-art techniques and to other RIM solutions, with both synthetic and real signals, showing remarkable results.

摘要

卫星导航在商业应用和关键基础设施中都很流行,它提供了精确的位置和时间参考。因此,对这些系统的干扰可能会对众多领域产生影响。此外,隐私保护设备(PPD)—干扰设备—相对便宜且易于获得,可能会在广泛的地理区域内拒绝服务。当前的干扰缓解技术基于干扰消除方法,需要检测和估计干扰波形。最近,提出了稳健干扰缓解(RIM)框架,该框架通过将干扰信号视为异常值,利用稳健统计学的结果。它具有拒绝干扰信号而无需检测或估计其波形的优点。在本文中,我们将该框架扩展到干扰器在时域以外的某些变换域中稀疏的情况。此外,我们分析了 Huber 非线性在 RIM 中的应用,并得出了其效率损失。我们将其性能与最先进的技术和其他 RIM 解决方案进行了比较,包括合成和真实信号,结果非常显著。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c377/6068611/0cf68eed9b31/sensors-18-02217-g001.jpg

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