Dual-Satellite Doppler Accuracy Prediction and Geometry Selection for Sparse LEO Signals of Opportunity

Qi Liu, Marc Fernández-Temprado, Antoni Reus-Bergas, Shuguo Pan, Wang Gao, Gonzalo Seco-Granados, José A. López-Salcedo

Low Earth Orbit (LEO) satellites have emerged as a promising complement to GNSS for positioning in signal challenged environments. In sparse LEO signals of opportunity scenarios, Doppler positioning often relies on only one or two satellite passes, making positioning accuracy highly dependent on pass geometry. This paper investigates dual satellite LEO Doppler accuracy prediction and geometry selection. A single pass Doppler accuracy model based on the Doppler Dilution of Precision (DDOP) framework is first validated using real Iridium measurements. An information domain fusion model is then developed to combine the effective position information from two satellite passes while accounting for pass specific clock parameters. Based on this model, an analytical relationship between the intersection angle of the two predicted error ellipses and the fused positioning accuracy is derived and verified through simulations. Long term ORBCOMM observations are further used to evaluate the practical availability of favorable satellite pairs. Results show that an intersection angle of about 20° is sufficient to achieve approximately 50 m theoretical positioning accuracy, and that such complementary satellite pairs are typically available within about 30 min. These results provide practical guidance for geometry aware satellite selection and observation scheduling in sparse LEO Doppler positioning.