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Proceedings Paper

Distributed sensor management for space situational awareness via a negotiation game
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Paper Abstract

Space situational awareness (SSA) is critical to many space missions serving weather analysis, communications, and navigation. However, the number of sensors used in space situational awareness is limited which hinders collision avoidance prediction, debris assessment, and efficient routing. Hence, it is critical to use such sensor resources efficiently. In addition, it is desired to develop the SSA sensor management algorithm in a distributed manner. In this paper, a distributed sensor management approach using the negotiation game (NG-DSM) is proposed for the SSA. Specifically, the proposed negotiation game is played by each sensor and its neighboring sensors. The bargaining strategies are developed for each sensor based on negotiating for accurately tracking desired targets (e.g., satellite, debris, etc.) . The proposed NG-DSM method is tested in a scenario which includes eight space objects and three different sensor modalities which include a space based optical sensor, a ground radar, or a ground Electro-Optic sensor. The geometric relation between the sensor, the Sun, and the space object is also considered. The simulation results demonstrate the effectiveness of the proposed NG-DSM sensor management methods, which facilitates an application of multiple-sensor multiple-target tracking for space situational awareness.

Paper Details

Date Published: 22 May 2015
PDF: 11 pages
Proc. SPIE 9469, Sensors and Systems for Space Applications VIII, 94690K (22 May 2015); doi: 10.1117/12.2177958
Show Author Affiliations
Bin Jia, Intelligent Fusion Technology, Inc. (United States)
Dan Shen, Intelligent Fusion Technology, Inc. (United States)
Khanh Pham, Air Force Research Lab. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Genshe Chen, Intelligent Fusion Technology, Inc. (United States)


Published in SPIE Proceedings Vol. 9469:
Sensors and Systems for Space Applications VIII
Khanh D. Pham; Genshe Chen, Editor(s)

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