Momentum enhancement factor estimation for asteroid redirect missions

Abstract

An asteroid mitigation demonstration mission is gaining interest among the planetary defense community to better understand the challenges and the dynamics of a small solar system body (SB) impact scenario. The Kinetic Impactor (KI) deflection technique, considered the most mature and cost effective approach for deflecting SBs, gained credibility following both the numerous studies performed (Don Quijote, NEOShield-2, preparations for DART mission, …) as well as the successful targeting of the Deep Impact (DI) spacecraft (S/C) into comet 9 P/Tempel 1. A dual-satellite concept AIDA with KI (DART) and an Explorer S/C (AIM/HERA) is currently under study by the ESA and NASA. While one of the more mature deflection options, there are still a significant number of poorly constrained aspects of the KI deflection technique. Of particular interest are the complex ejecta cloud dynamics that can have a considerable impact on the deflection efficiency and the according β-factor. Understanding the momentum enhancement β-factor is considered paramount as it bears the potential of overall mission cost reduction and is inherently linked to the SB geotechnical properties. Therefore, estimating this β-factor is one of the top-level scientific requirements for future demonstration missions. First, this work presents a β-factor estimation technique with the focus on an SB orbit determination (OD) filter where radioscience tracking data of an Explorer S/C at the close proximity is fused with optical navigation information. Second, an extensive error analysis is presented where the major drivers of the β-factor error budget are identified based on a breakdown tree. The paper shows the estimation filter architecture and explicitly addresses the data fusion process. An extensive, high fidelity test campaign has been conducted to conclude on the achievable β-factor estimation performance for a KI impactor reference scenario with the SB 2001 QC34. An end-to-end momentum enhancement factor estimation technique is presented and it was found that the β-factor uncertainty is reduced to 0.33 (3σ) after only 1 week of monitoring with 67% availability of the tracking stations and a station-keeping manoeuver once a day. This estimation performance has shown that the momentum enhancement factor uncertainties can be constrained considerably and thus further advocates a KI demonstration mission.