RFI and Jamming Detection in Antenna Arrays with an LSTM Autoencoder

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Ntemkas, Christos, Argyriou, Antonios
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866909709093568512
author Ntemkas, Christos
Argyriou, Antonios
author_facet Ntemkas, Christos
Argyriou, Antonios
contents Radio frequency interference (RFI) and malicious jammers are a significant problem in our wireless world. Detecting RFI or jamming is typically performed with model-based statistical detection or AI-empowered algorithms that use an input baseband data or time-frequency representations like spectrograms. In this work we depart from the previous approaches and we leverage data in antenna array systems. We use Fourier imaging to localize spatially the sources and then deploy a deep LSTM autoencoder that detects RFI and jamming as anomalies. Our results for different power levels of the RFI/jamming sources, and the signal of interest, reveal that our detector offers high performance without needing any pre-existing knowledge regarding the RFI or jamming signal.
format Preprint
id arxiv_https___arxiv_org_abs_2507_20648
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle RFI and Jamming Detection in Antenna Arrays with an LSTM Autoencoder
Ntemkas, Christos
Argyriou, Antonios
Signal Processing
Radio frequency interference (RFI) and malicious jammers are a significant problem in our wireless world. Detecting RFI or jamming is typically performed with model-based statistical detection or AI-empowered algorithms that use an input baseband data or time-frequency representations like spectrograms. In this work we depart from the previous approaches and we leverage data in antenna array systems. We use Fourier imaging to localize spatially the sources and then deploy a deep LSTM autoencoder that detects RFI and jamming as anomalies. Our results for different power levels of the RFI/jamming sources, and the signal of interest, reveal that our detector offers high performance without needing any pre-existing knowledge regarding the RFI or jamming signal.
title RFI and Jamming Detection in Antenna Arrays with an LSTM Autoencoder
topic Signal Processing
url https://arxiv.org/abs/2507.20648