Rapid orbital characterization of local area space objects utilizing image-differencing techniques

Paul D. McCall; Madeleine L. Naudeau; Marlon E. Sorge; Thomas Farrell; Malek Adjouadi

doi:10.1117/12.2017888

21 May 2013 Rapid orbital characterization of local area space objects utilizing image-differencing techniques

Paul D. McCall, Madeleine L. Naudeau, Marlon E. Sorge, Thomas Farrell, Malek Adjouadi

Proceedings Volume 8739, Sensors and Systems for Space Applications VI; 873908 (2013) https://doi.org/10.1117/12.2017888
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Satellites have limited awareness of nearby objects that might pose a collision hazard. Small, relatively inexpensive onboard optical local area sensors have been proposed as a means of providing additional awareness. However, such sensors often have limited performance. Proposed are methods to increase the Local Area Awareness provided by such sensors by means of classical and novel image processing techniques. The local area of the sensor platform is defined, for our purposes, as a sphere of radius 500 km surrounding the sensor platform, or observing satellite. This analysis utilizes image differencing-based techniques, in the development of a detection algorithm and proposes a novel objectvelocity classifier. This classifier may provide a means of rapidly distinguishing local area objects that pose a possible collision hazard when an orbital two-line element set is not available. Derivation of a novel classifier is based on the speed of the projected object moving across the focal plane array of the detector. This technique relies on the assumption that detection from the sensor platform allows for tracking of the object over all times the object is within the local area of the sensor platform. This alternative to intensity-based, signalto- noise ratio detection methods is performed by exploiting the stellar background as a reference from a space-based observing satellite. Results presented in this paper further demonstrate the ability of the proposed classifier to provide a means of rapidly distinguishing objects that pose a possible hazard within the local area of the sensor platform. These preliminary results act to substantiate this claim and therefore lay out a pathway for relevant and meaningful future work in the area of Local Area Awareness for satellites.

Citation Download Citation

Paul D. McCall, Madeleine L. Naudeau, Marlon E. Sorge, Thomas Farrell, and Malek Adjouadi "Rapid orbital characterization of local area space objects utilizing image-differencing techniques", Proc. SPIE 8739, Sensors and Systems for Space Applications VI, 873908 (21 May 2013); https://doi.org/10.1117/12.2017888

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