Hasib, M.; Kandeepan, S.; Rowe, W.S.T.; Al-Hourani, A. Direction-of-Arrival (DoA) Estimation Performance for Satellite Applications in a Multipath Environment with Rician Fading and Spatial Correlation. Sensors2023, 23, 5458.
Hasib, M.; Kandeepan, S.; Rowe, W.S.T.; Al-Hourani, A. Direction-of-Arrival (DoA) Estimation Performance for Satellite Applications in a Multipath Environment with Rician Fading and Spatial Correlation. Sensors 2023, 23, 5458.
Hasib, M.; Kandeepan, S.; Rowe, W.S.T.; Al-Hourani, A. Direction-of-Arrival (DoA) Estimation Performance for Satellite Applications in a Multipath Environment with Rician Fading and Spatial Correlation. Sensors2023, 23, 5458.
Hasib, M.; Kandeepan, S.; Rowe, W.S.T.; Al-Hourani, A. Direction-of-Arrival (DoA) Estimation Performance for Satellite Applications in a Multipath Environment with Rician Fading and Spatial Correlation. Sensors 2023, 23, 5458.
Abstract
The Direction-of-Arrival (DoA) estimation methods are highly versatile and find extensive applications in satellite communication. The DoA methods are employed across a range of orbits, from Low Earth Orbits (LEO) to Geostationary Earth Orbits (GEO). They serve multiple applications, including altitude determination, geolocation and estimation accuracy, target localization, and relative and collaborative positioning. This paper presents a novel approach for modeling the DoA angle using a closed-form expression, incorporating the boresight angle and satellite and Earth station position data. The method uses the geographic coordinate system in the satellite communication system, precisely the latitude and longitude of the Earth station and altitude parameters of the satellite stations, to calculate the Earth station’s elevation angle and accurately model the DoA angle. Furthermore, this paper performs a comprehensive comparative analysis of various DoA methods to gain deeper insights into the performance of DoA estimation in multi-antenna systems operating under spatially correlated channels. Accordingly, this paper evaluates DoA estimation performance using root-mean-square-error (RMSE) statistics for uplink and downlink conditions through extensive Monte Carlo simulations. The simulation’s effectiveness is validated against the Cramer-Rao Bound (CRB) performance metric for the Additive white Gaussian noise (AWGN) case. (i.e., thermal noise). The simulation results demonstrate improved RMSE performance in satellite systems by incorporating spatial correlation into the system model.
Keywords
Direction of Arrival (DoA) Estimation; Multipath Environment; Geostationary Earth Orbit (GEO); Low Earth Orbit (LEO); and Spatial Correlation
Subject
Engineering, Telecommunications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
