Title

Fusion Methodologies for Orbit Determination with Distributed Sensor Networks

Abstract

Given that a single ground-based sensor, such as a radar or electro-optical telescope, is limited to observing only a small portion of an object's orbit, tracking accuracy can be greatly improved by collecting data with multiple geographically disparate sensors. Processing the data provided by such a distributed sensor network, however, poses complications in that full cooperation, i.e. Direct sharing of raw measurement data, is usually implausible. Alternatively, cooperation within the network can be more feasibly established by instead sharing the posterior state densities produced by each sensor's tracking scheme and fusing these densities directly. This paper investigates the use of geometric averaging approaches to probability density fusion to exploit the diversity of a cooperative, distributed sensor network. These methods not only require approximate methods to perform sensor fusion, but they also require numerical procedures to determine an ideal weighting for each density. Computationally efficient approximations to these fusion techniques are formulated and compared to more expensive methods to determine the efficacy of the approximations. A numerical simulation considering the tracking of a space object in low Earth orbit with three cooperating ground-based radar stations is presented to produce conclusions on the discussed approaches.

Meeting Name

21st International Conference on Information Fusion, FUSION 2018 (2018: Jul. 10-13, Cambridge, UK)

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Data handling; Earth (planet); Information fusion; Numerical methods; Probability density function; Radar stations; Radar tracking; Sensor networks, Approximate methods; Computationally efficient; Distributed sensor networks; Ground based radar; Ground based sensors; Numerical procedures; Orbit determination; Probability densities, Orbits

International Standard Book Number (ISBN)

978-099645276-2

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2018 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Share

 
COinS