Complexity-Scalable Direct Geolocation and Cancellation of Terrestrial GNSS Jammers: Single-Satellite and Multi-Antenna Experiments in Low Earth Orbit

Abstract

Monitoring the radio-frequency (RF) spectrum from space imposes demanding requirements to satellite platforms in terms of communication bandwidth and computational resources, which are necessary for the downlink, the storage, and the processing of high-throughput I/Q samples. This paper analyzes in depth the quasi-direct geolocation (QDG) as a technique to enable the exploitation of satellites of opportunity in low Earth orbit (LEO) to sense the spectrum in the bands of global navigation satellite systems (GNSS). This is a technique of passive RF geolocation and consists of an ensemble of signal processing algorithms, which compress the I/Q samples and process the compressed data through fast delay-Doppler shift matching and interferometry in a quantized time-frequency domain. These algorithms speed up the exhaustive search of multiple RF sources in the position domain. The efficiency gain addresses the bottleneck that prevents the employment of satellites, which are limited in downlink capacity and on-board computational power. These satellites are usually constrained in size, weight and power (SWaP) and represent most of the spacecrafts in LEO. The ability to exploit assets as such for the geolocation of terrestrial GNSS jammers in near real time is instrumental the performance of a multi-constellation GNSS RFI monitoring system. The present work describes the mathematical framework and precision bounds, introduces single- and multi-antenna uses cases, combines different compression methods, and evaluates the geolocation accuracy with real data. The I/Q samples were collected by a repurposed GNSS reflectometry (GNSS-R) satellite, OPS-SAT PRETTY, in a dedicated test session during Jammertest 2025. The experimental results demonstrate the capability to geolocate GNSS jammers with different signal-to-noise ratios (SNR) with extremely high compression ratios.