Radiometric Interferometry for Deep Space Navigation Using Geostationary Satellites

Deep space navigation, defined as spacecraft position tracking beyond the lunar orbit, presents significant challenges due to the extremely weak Global Navigation Satellite System (GNSS) signals and severe signal attenuation over interplanetary distances. Traditional terrestrial systems, such as NASA’s Deep Space Network (DSN) and ESA’s ESTRACK, rely on Very Long Baseline Interferometry (VLBI) for angular positioning. However, these systems are limited by relatively short baselines, atmospheric distortions requiring extensive calibration, and reduced line-of-sight (LOS) availability due to Earth’s rotation. Because VLBI angle measurements require at least two simultaneously visible stations, the measurement duty cycle is inherently constrained. This research proposes a complementary deep space navigation approach using space-based interferometry, in which radio signals from the spacecraft are received and cross-correlated onboard Geostationary Earth Orbit (GEO) satellites. By replacing terrestrial VLBI stations with dual GEO platforms, the method significantly extends the effective baseline, removes atmospheric phase errors, and provides near-continuous visibility to deep space targets. Unlike Earth-based systems, GEO-based interferometry maintains persistent mutual visibility between stations, enabling higher measurement availability and more flexible mission support. A complete system model is presented, including the principles of dual-frequency phase-based angular tracking and a structured error budget analysis. Theoretical error analysis indicates that the GEO-based system achieves a total angular error better than 4 nanoradians—within the same order of magnitude as terrestrial VLBI. In particular, the space-based architecture nearly doubles the geometric availability for interferometric tracking while eliminating the need for atmospheric calibration. These results support the feasibility of the GEO-based VLBI concept and motivate continued research, including detailed simulations, hardware implementation, and field validation.