Future exploration missions will be likely exploited by several probes operating in the same scenario at the same time. In order to simplify as much as possible the probes’ architecture, the navigation function can be centralized in a mother spacecraft. Performance of the navigation subsystem are fundamental to correctly close the probes’ guidance loop. The paper focuses on the estimation technique to be used to track these multiple targets when the risk of wrong attribution, due to the crowded scenario, is considered. The guidance law used as a basis for the computation is given by the artificial potential function method, to be implemented as a closed loop in which the state provided by several estimators is introduced as input. This work shows how to deal with several measurements, including an attribution capability in the framework of recursive estimators. Two solutions, namely Joint Probability Density Association and Joint Probability Density Association in Particle filters, are discussed and compared. From the simulations carried out, both the approaches look successful in managing the co-presence of several targets. Computation time makes the JPDA the preferred solution, while the original JPDAP should better perform in strongly nonlinear conditions, concerning either dynamics or observation.

Guidance and Navigation for Fleets of Landing Probes / Reali, Fabrizio; Palmerini, Giovanni Battista; Sgubini, Silvano. - ELETTRONICO. - (2009), pp. 1-17. (Intervento presentato al convegno XX Congresso Nazionale AIDAA tenutosi a Milano nel 29 giugno - 3 luglio 2009).

Guidance and Navigation for Fleets of Landing Probes

REALI, FABRIZIO;PALMERINI, Giovanni Battista;SGUBINI, SILVANO
2009

Abstract

Future exploration missions will be likely exploited by several probes operating in the same scenario at the same time. In order to simplify as much as possible the probes’ architecture, the navigation function can be centralized in a mother spacecraft. Performance of the navigation subsystem are fundamental to correctly close the probes’ guidance loop. The paper focuses on the estimation technique to be used to track these multiple targets when the risk of wrong attribution, due to the crowded scenario, is considered. The guidance law used as a basis for the computation is given by the artificial potential function method, to be implemented as a closed loop in which the state provided by several estimators is introduced as input. This work shows how to deal with several measurements, including an attribution capability in the framework of recursive estimators. Two solutions, namely Joint Probability Density Association and Joint Probability Density Association in Particle filters, are discussed and compared. From the simulations carried out, both the approaches look successful in managing the co-presence of several targets. Computation time makes the JPDA the preferred solution, while the original JPDAP should better perform in strongly nonlinear conditions, concerning either dynamics or observation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/211583
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