Mars is capturing attention since many decades, as witnessed by the numerous robotic missions flown so far. The proposed architecture exploits the gravitational field asymmetry generated by Mars’s moon Phobos to guarantee state self-reconstruction with only relative measures. Moreover, by adding relative measurements of a user satellite, its state can be reconstructed starting from an initial guess and its uncertainty. The paper critically presents the adopted approach to settle the constellation design, motivating both drivers and degrees of freedom selection. In particular, trajectories asymmetry and relative state observability maximization drove the trajectory alternatives trade-off, together with the number of required space assets in the constellation minimization; alternatives grew up from periodic trajectory families obtained by numerical continuation schemes led by energy variation and applied on the analytical third-order approximation for the three-body dynamics. The Navigation System (NS) is presented: an architecture concept that exploits the field’s asymmetry generated by Phobos to reconstruct the user’s state through a measurements history fed into a Square Root - Unscented Kalman Filter (SR-UKF). The proposed approach effectiveness is discussed through performance obtained on state reconstruction for constellation elements self-calibration first and as navigation service output, towards users, then. Finally, the Trilateration System (TS) is built: a constellation configuration that self-calibrates its position and uses the state knowledge to compute the user’s position using pseudo-range measurements (trilateration). The uncertainties of the system’s satellites positions are computed and their effects on the user position accuracy are evaluated, taking into account the system Position-Diluition Of Precision (PDOP) given by the constellation’s geometric properties. Obtained results are promising for both the architecture concepts.
Mars-Phobos Multi-Body Regime Exploitation for Martian Navigation Light Constellation Design
Barberi Spirito, D.;Lavagna, M.
2021-01-01
Abstract
Mars is capturing attention since many decades, as witnessed by the numerous robotic missions flown so far. The proposed architecture exploits the gravitational field asymmetry generated by Mars’s moon Phobos to guarantee state self-reconstruction with only relative measures. Moreover, by adding relative measurements of a user satellite, its state can be reconstructed starting from an initial guess and its uncertainty. The paper critically presents the adopted approach to settle the constellation design, motivating both drivers and degrees of freedom selection. In particular, trajectories asymmetry and relative state observability maximization drove the trajectory alternatives trade-off, together with the number of required space assets in the constellation minimization; alternatives grew up from periodic trajectory families obtained by numerical continuation schemes led by energy variation and applied on the analytical third-order approximation for the three-body dynamics. The Navigation System (NS) is presented: an architecture concept that exploits the field’s asymmetry generated by Phobos to reconstruct the user’s state through a measurements history fed into a Square Root - Unscented Kalman Filter (SR-UKF). The proposed approach effectiveness is discussed through performance obtained on state reconstruction for constellation elements self-calibration first and as navigation service output, towards users, then. Finally, the Trilateration System (TS) is built: a constellation configuration that self-calibrates its position and uses the state knowledge to compute the user’s position using pseudo-range measurements (trilateration). The uncertainties of the system’s satellites positions are computed and their effects on the user position accuracy are evaluated, taking into account the system Position-Diluition Of Precision (PDOP) given by the constellation’s geometric properties. Obtained results are promising for both the architecture concepts.| File | Dimensione | Formato | |
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