Satellite Visibility Window Estimation Using Doppler Measurement for IoT Applications

Many Internet-of-Things (IoT)-over-satellite applications rely on affordable location-aware but energy-constrained IoT sensors. In this letter, we propose a novel method to estimate the satellite visibility window in IoT devices based on simple Doppler measurements. We present two scenarios where the orbital information of the serving satellite is initially unknown to the IoT device: (i) we assume that the geographic coordinates are known to the IoT device, and (ii) we assume that the coordinates are completely unknown. Accordingly, we derive the Doppler measurement likelihood function, and simplify it to a root mean square error (RMSE) minimization problem. From a sequence of Doppler measurements, we estimate the orbital parameters of the serving satellite using a stochastic optimizer to minimize the RMSE. From the orbital estimation, we then predict the satellite visibility window (satellite pass). To gauge the accuracy of the window estimation, we apply the intersection-over-union metric to compute the overlapping visibility window between the ground truth and the estimation, and consequently present the results based on extensive Monte Carlo simulations.

Automated summary

In this letter, we propose a novel method to estimate the satellite visibility window in IoT devices based on simple Doppler measurements. We derive the Doppler measurement likelihood function and simplify it to an RMSE minimization problem. Using a stochastic optimizer, we estimate the orbital parameters of the serving satellite and predict the satellite visibility window. We evaluate the accuracy of the window estimation through Monte Carlo simulations and the intersection-over-union metric.