This paper investigates the performance of the forthcoming lunar navigation satellite systems for estimating not only the position of an onboard receiver in a lunar inertial reference frame but also, and with a consistent accuracy, the relative position between two or more spacecraft in proximity. This could be the case of two spacecraft performing a rendezvous, of a lander released by an orbiter, or the case of the permanent relative navigation service for a formation of satellites around the Moon. The considered observables are the pseudorange and pseudorange-rate measurements provided by the upcoming lunar communication and navigation system (LCNS), expected to support lunar missions. A single-stage Kalman filter is implemented, and its performance is demonstrated through error statistics, which are then compared to what can be achieved with sequential filtering.
Filtering Strategies for Relative Navigation in Lunar Scenarios Using LCNS / Sabatini, M.; Palmerini, G. B.. - In: AEROSPACE. - ISSN 2226-4310. - 11:1(2024), pp. 1-17. [10.3390/aerospace11010059]
Filtering Strategies for Relative Navigation in Lunar Scenarios Using LCNS
Sabatini M.
Primo
;Palmerini G. B.Secondo
2024
Abstract
This paper investigates the performance of the forthcoming lunar navigation satellite systems for estimating not only the position of an onboard receiver in a lunar inertial reference frame but also, and with a consistent accuracy, the relative position between two or more spacecraft in proximity. This could be the case of two spacecraft performing a rendezvous, of a lander released by an orbiter, or the case of the permanent relative navigation service for a formation of satellites around the Moon. The considered observables are the pseudorange and pseudorange-rate measurements provided by the upcoming lunar communication and navigation system (LCNS), expected to support lunar missions. A single-stage Kalman filter is implemented, and its performance is demonstrated through error statistics, which are then compared to what can be achieved with sequential filtering.File | Dimensione | Formato | |
---|---|---|---|
Sabatini_Filtering_2024.pdf
accesso aperto
Tipologia:
Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza:
Creative commons
Dimensione
6.83 MB
Formato
Adobe PDF
|
6.83 MB | Adobe PDF |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.