Efficient Multi-Sensor Data Fusion for Space Surveillance


Multi-sensor networks can extend the sensing region of a single sensor in order to provide a more geometrically diverse and comprehensive view of the state of a dynamical system. The use of a multi-sensor network gives rise to the need for a fusion step that combines the outputs of all sensor nodes into a single probabilistic state description. This paper examines a fusion method based on logarithmic opinion pools and develops algorithms for multi-sensor data fusion as well as investigates weight selection schemes for the opinion pool using efficient quadrature integration methods. The proposed fusion rules are applied to the tracking of a space object using multiple ground-based optical sensors. It is shown that the multi-sensor fusion rule leads to an increase of nearly two orders of magnitude in the position tracking accuracy as compared to the traditional single-sensor tracking method.

Meeting Name

American Control Conference (2015: Jul. 1-3, Chicago, IL)


Mechanical and Aerospace Engineering

Keywords and Phrases

Data fusion; Dynamical systems; Sensor networks; Sensor nodes; Space surveillance; Tracking (position); Integration method; Multi-sensor fusion; Multi-sensor networks; Multiple grounds; Multisensor data fusion; Orders of magnitude; Selection scheme; Tracking method; Sensor data fusion

International Standard Book Number (ISBN)


International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version


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© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jul 2015