# Low-Cost COTS GNSS Interference Monitoring, Detection, and Classification System +
###### Abstract  
Interference signals cause position errors and outages to global navigation satellite system (GNSS) receivers. However, to solve these problems, the interference source must be detected, classified, its purpose determined, and localized to eliminate it. Several interference monitoring solutions exist, but these are expensive, resulting in fewer nodes that may miss spatially sparse interference signals. This article introduces a low-cost commercial-off-the-shelf (COTS) GNSS interference monitoring, detection, and classification receiver. It employs machine learning (ML) on tailored signal pre-processing of the raw signal samples and GNSS measurements to facilitate a generalized, high-performance architecture that does not require human-in-the-loop (HIL) calibration. Therefore, the low-cost receivers with high performance can justify significantly more receivers being deployed, resulting in a significantly higher probability of intercept (POI). The architecture of the monitoring system is described in detail in this article, including an analysis of the energy consumption and optimization. Controlled interference scenarios demonstrate detection and classification capabilities exceeding conventional approaches. The ML results show that accurate and reliable detection and classification are possible with COTS hardware. Global navigation satellite system (GNSS); interference; detection; classification; machine learning; commercial-off-the-shelf (COTS) +
Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))). Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/0](https://creativecommons.org/licenses/by/4.0/0)]([https://creativecommons.org/licenses/by/4.0/0](https://creativecommons.org/licenses/by/4.0/0))). Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))). Footnote †: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons. Several interference monitoring systems exist [2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23; 24; 25; 26; 27; 28; 29]. There is also an attempt to standardize monitoring approaches [30]. Several systems are developed to be low-cost [3; 11; 13] or to use software-defined radio (SDR) techniques [3; 4; 13; 15]. However, these systems tend to be expensive purpose-built equipment. As a result, the number of monitoring receivers is too low to be effective. A common strategy is to mount these systems near other critical infrastructures, such as fixed installations on highways [20; 24; 26], airports [2; 18; 27; 28], or existing geodetic reference networks [6; 7; 8; 25; 29], which makes these more effective. A fascinating approach is a monitoring station onboard the international space station (ISS) [21]. Low earth orbit (LEO) satellites cover a larger geographic area to monitor, but are significantly more expensive than current launch costs and may have reduced sensitivity if an interference transmitter antenna suppresses the output signal at higher elevation angles. Therefore, an ideal monitoring system should cover a large geographic area with significantly reduced costs. There are many different interference waveforms [31; 32], and the purpose and intent of the interference signal are determined by knowing what the waveform is.