International Journal of Aeronautical and Space Sciences

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Intentional GNSS Interference Detection and Characterization Algorithm Using AGC and Adaptive IIR Notch Filter

  • Yang, Jeong Hwan (School of Mechanical and Aerospace Engineering/Automation and System Research Institute/The Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Kang, Chang Ho (School of Mechanical and Aerospace Engineering/Automation and System Research Institute/The Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Kim, Sun Young (School of Mechanical and Aerospace Engineering/Automation and System Research Institute/The Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Park, Chan Gook (School of Mechanical and Aerospace Engineering/Automation and System Research Institute/The Institute of Advanced Aerospace Technology, Seoul National University)
  • Received : 2012.09.04
  • Accepted : 2012.11.21
  • Published : 2012.12.30
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Abstract

A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft's precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.

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References

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