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GNSS Radio Frequency Interference Monitoring from LEO Satellites: An In-Laboratory Prototype.

Micaela Troglia Gamba¹, Brendan David Polidori¹, Alex Minetto²

¹LINKS Foundation, 10138 Turin, Italy.

Sensors (Basel, Switzerland)

|January 23, 2024

Summary

A new nanosatellite system effectively detects and classifies terrestrial radio frequency interference (RFI) impacting global navigation satellite system (GNSS) signals. This system uses two algorithms to identify jamming and spoofing, showing promising results for civil RFI monitoring.

Keywords:

GNSS radio frequency interference LEO advanced RISC machine (ARM) processors embedded platform jamming software spoofing

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Area of Science:

Space Science
Signal Processing
Navigation Systems

Background:

Radio frequency interference (RFI) significantly disrupts global navigation satellite system (GNSS) signals.
Low-Earth orbit (LEO) satellites offer a promising platform for GNSS RFI monitoring.
Recent years have seen increased interest and initiatives in LEO-based RFI detection.

Purpose of the Study:

To propose and implement a spaceborne system for detecting, classifying, and localizing terrestrial GNSS RFI, specifically jamming and spoofing.
To develop a software module for RFI detection suitable for nanosatellite deployment.
To evaluate the performance and computational load of the implemented RFI detection algorithms.

Main Methods:

Development of a software module for RFI detection on a nanosatellite platform.
Implementation of two distinct RFI detection algorithms: chi-square goodness-of-fit (GoF) for non-GNSS-like interference (e.g., chirp jamming) and snapshot acquisition for GNSS-like interference (e.g., spoofing).
Evaluation of detection performance, sensitivity, and computational load through preliminary testing.

Main Results:

The implemented system demonstrates promising detection capabilities for both jamming and spoofing signals.
Preliminary tests show good sensitivity in identifying RFI.
Analysis indicates areas for computational load optimization, particularly for the snapshot acquisition detector.

Conclusions:

The developed nanosatellite-based RFI detection system shows potential for civil use in monitoring terrestrial GNSS interference.
The chi-square GoF and snapshot acquisition algorithms provide effective means for detecting different types of RFI.
Further optimization of computational load is recommended for enhanced efficiency, especially for the snapshot acquisition method.