Decentralized Fusion with Finite Set Statistics for Landing Navigation


The simultaneous localization and mapping (SLAM) problem is one that utilizes a vehicle's observations of its environment to refine an estimate of that environment while improving understanding of its own state. This paper proposes the use of SLAM tools formulated using finite set statistics to perform terrain-aided navigation for planetary landers. Further, the methodology is designed to augment, rather than replace, standard extended Kalman filter-based navigation architectures via decentralized fusion with feedback, enabling a SLAM-Fusion procedure with substantially lower development costs than replacing existing approaches altogether. The resulting approach enables significant performance improvements in existing navigation filters with little to no modification of the existing scheme. The theoretical results are supported via simulation of a lunar descent trajectory and the proposed SLAM-Fusion procedure.

Meeting Name

AAS/AIAA Astrodynamics Specialist Conference, 2017 (2017: Aug. 20-24, Stevenson, WA)


Mechanical and Aerospace Engineering

Keywords and Phrases

Astrophysics; Kalman filters; Navigation; Planetary landers; Robotics; Set theory, Decentralized fusions; Descent trajectories; Finite set statistics; Navigation architectures; Navigation filters; Performance improvements; Simultaneous localization and mapping problems; Terrain aided navigation, Air navigation

International Standard Book Number (ISBN)


International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version


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Publication Date

01 Aug 2018

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