GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918274855337984 |
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| author | Heublein, Lucas Nowak, Thorsten Feigl, Tobias Pahl, Jaspar Ott, Felix |
| author_facet | Heublein, Lucas Nowak, Thorsten Feigl, Tobias Pahl, Jaspar Ott, Felix |
| contents | Jamming devices disrupt signals from the global navigation satellite system (GNSS) and pose a significant threat by compromising the reliability of accurate positioning. Consequently, the detection and localization of these interference signals are essential to achieve situational awareness, mitigating their impact, and implementing effective countermeasures. In this paper, we utilize a two-times-two patch antenna system (i.e., the software defined radio device Ettus USRP X440) to predict the angle, elevation, and distance to the jamming source based on in-phase and quadrature (IQ) samples. We propose to use an inertial measurement unit (IMU) attached to the antenna system to predict the relative movement of the antenna in dynamic scenarios. We present a synthetic aperture system that enables coherent spatial imaging using platform motion to synthesize larger virtual apertures, offering superior angular resolution without mechanically rotating antennas. While classical angle-of-arrival (AoA) methods exhibit reduced accuracy in multipath environments due to signal reflections and scattering, leading to localization errors, we utilize a methodology that fuses IQ and Fast Fourier Transform (FFT)-computed spectrograms with 22 AoA features and the predicted relative movement to enhance GNSS jammer direction finding. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2512_05128 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System Heublein, Lucas Nowak, Thorsten Feigl, Tobias Pahl, Jaspar Ott, Felix Signal Processing Artificial Intelligence Jamming devices disrupt signals from the global navigation satellite system (GNSS) and pose a significant threat by compromising the reliability of accurate positioning. Consequently, the detection and localization of these interference signals are essential to achieve situational awareness, mitigating their impact, and implementing effective countermeasures. In this paper, we utilize a two-times-two patch antenna system (i.e., the software defined radio device Ettus USRP X440) to predict the angle, elevation, and distance to the jamming source based on in-phase and quadrature (IQ) samples. We propose to use an inertial measurement unit (IMU) attached to the antenna system to predict the relative movement of the antenna in dynamic scenarios. We present a synthetic aperture system that enables coherent spatial imaging using platform motion to synthesize larger virtual apertures, offering superior angular resolution without mechanically rotating antennas. While classical angle-of-arrival (AoA) methods exhibit reduced accuracy in multipath environments due to signal reflections and scattering, leading to localization errors, we utilize a methodology that fuses IQ and Fast Fourier Transform (FFT)-computed spectrograms with 22 AoA features and the predicted relative movement to enhance GNSS jammer direction finding. |
| title | GNSS Jammer Direction Finding in Dynamic Scenarios Using an Inertial-based Multi-Antenna System |
| topic | Signal Processing Artificial Intelligence |
| url | https://arxiv.org/abs/2512.05128 |