Your browser doesn't support javascript.
loading
GNSS Radio Frequency Interference Monitoring from LEO Satellites: An In-Laboratory Prototype.
Troglia Gamba, Micaela; Polidori, Brendan David; Minetto, Alex; Dovis, Fabio; Banfi, Emilio; Dominici, Fabrizio.
Afiliación
  • Troglia Gamba M; LINKS Foundation, 10138 Turin, Italy.
  • Polidori BD; LINKS Foundation, 10138 Turin, Italy.
  • Minetto A; Department of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Turin, Italy.
  • Dovis F; Department of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Turin, Italy.
  • Banfi E; Italspazio S.r.l., San Giovanni La Punta, 95037 Catania, Italy.
  • Dominici F; LINKS Foundation, 10138 Turin, Italy.
Sensors (Basel) ; 24(2)2024 Jan 13.
Article en En | MEDLINE | ID: mdl-38257601
ABSTRACT
The disruptive effect of radio frequency interference (RFI) on global navigation satellite system (GNSS) signals is well known, and in the last four decades, many have been investigated as countermeasures. Recently, low-Earth orbit (LEO) satellites have been looked at as a good opportunity for GNSS RFI monitoring, and the last five years have seen the proliferation of many commercial and academic initiatives. In this context, this paper proposes a new spaceborne system to detect, classify, and localize terrestrial GNSS RFI signals, particularly jamming and spoofing, for civil use. This paper presents the implementation of the RFI detection software module to be hosted on a nanosatellite. The whole development work is described, including the selection of both the target platform and the algorithms, the implementation, the detection performance evaluation, and the computational load analysis. Two are the implemented RFI detectors the chi-square goodness-of-fit (GoF) algorithm for non-GNSS-like interference, e.g., chirp jamming, and the snapshot acquisition for GNSS-like interference, e.g., spoofing. Preliminary testing results in the presence of jamming and spoofing signals reveal promising detection capability in terms of sensitivity and highlight room to optimize the computational load, particularly for the snapshot-acquisition-based RFI detector.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Bases de datos: MEDLINE Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Italia