Geolocation of radio interference sources using simulated quantum annealing on a geostationary satellite

Geolocation of radio interference sources via satellite is essential for ensuring the reliability of space communication services, particularly as satellite networks become increasingly congested and vulnerable to interference. While many existing geolocation methods rely on multi-satellite configurations, these approaches often require time and frequency synchronization or inter-satellite links, making them unsuitable for real-time scenarios. In this study, we focus on single-satellite geolocation based on direction-of-arrival (DOA) estimation using a multi-element antenna. To apply simulated quantum annealing (SQA), which has recently gained attention, the DOA estimation problem is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem and solved using annealing techniques. Sparse recovery is applied to spatial covariance matrices derived from array observations, and the resulting QUBO is solved via simulated annealing. Simulation results show that the proposed method outperforms conventional techniques such as beamformer and multiple signal classification (MUSIC), especially in low signal-to-noise power ratio (SNR) scenarios. For example, in a case where two signals arrive from random directions, the proposed method achieves a geolocation error of approximately 10 km at an SNR of 15 dB—about 1/10 that of Beamformer and 1/8 that of MUSIC—demonstrating its high resolution and robustness under constrained conditions.