An integrated approach to high-level information fusion
In today’s fast paced military operational environment, vast amounts of information must be sorted out and fused not only to allow commanders to make situation assessments, but also to support the generation of hypotheses about enemy force disposition and enemy intent. Current information fusion tec...
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| Veröffentlicht in: | Information fusion Jg. 10; H. 1; S. 25 - 50 |
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2009
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| Abstract | In today’s fast paced military operational environment, vast amounts of information must be sorted out and fused not only to allow commanders to make situation assessments, but also to support the generation of hypotheses about enemy force disposition and enemy intent. Current information fusion technology has the following two limitations. First, current approaches do not consider the battlefield context as a first class entity. In contrast, we consider situational context in terms of terrain analysis and inference. Second, there are no integrated and implemented models of the high-level fusion process. This paper describes the HiLIFE (High-Level Information Fusion Environment) computational framework for seamless integration of high levels of fusion (levels 2, 3 and 4). The crucial components of HiLIFE that we present in this paper are: (1) multi-sensor fusion algorithms and their performance results that operate in heterogeneous sensor networks to determine not only single targets but also force aggregates, (2) computational approaches for terrain-based analysis and inference that automatically combine low-level terrain features (such as forested areas, rivers, etc.) and additional information, such as weather, and transforms them into high-level militarily relevant abstractions, such as NO-GO, SLOW-GO areas, avenues of approach, and engagement areas, (3) a model for inferring adversary intent by mapping sensor readings of opponent forces to possible opponent goals and actions, and (4) sensor management for positioning intelligence collection assets for further data acquisition. The HiLIFE framework closes the loop on information fusion by specifying how the different components can computationally work together in a coherent system. Furthermore, the framework is inspired by a military process, the Intelligence Preparation of the Battlefield, that grounds the framework in practice. HiLIFE is integrated with a distributed military simulation system, OTBSAF, and the RETSINA multi-agent infrastructure to provide agile and sophisticated reasoning. In addition, the paper presents validation results of the automated terrain analysis that were obtained through experiments using military intelligence Subject Matter Experts (SMEs). |
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| AbstractList | In today’s fast paced military operational environment, vast amounts of information must be sorted out and fused not only to allow commanders to make situation assessments, but also to support the generation of hypotheses about enemy force disposition and enemy intent. Current information fusion technology has the following two limitations. First, current approaches do not consider the battlefield context as a first class entity. In contrast, we consider situational context in terms of terrain analysis and inference. Second, there are no integrated and implemented models of the high-level fusion process. This paper describes the HiLIFE (High-Level Information Fusion Environment) computational framework for seamless integration of high levels of fusion (levels 2, 3 and 4). The crucial components of HiLIFE that we present in this paper are: (1) multi-sensor fusion algorithms and their performance results that operate in heterogeneous sensor networks to determine not only single targets but also force aggregates, (2) computational approaches for terrain-based analysis and inference that automatically combine low-level terrain features (such as forested areas, rivers, etc.) and additional information, such as weather, and transforms them into high-level militarily relevant abstractions, such as NO-GO, SLOW-GO areas, avenues of approach, and engagement areas, (3) a model for inferring adversary intent by mapping sensor readings of opponent forces to possible opponent goals and actions, and (4) sensor management for positioning intelligence collection assets for further data acquisition. The HiLIFE framework closes the loop on information fusion by specifying how the different components can computationally work together in a coherent system. Furthermore, the framework is inspired by a military process, the Intelligence Preparation of the Battlefield, that grounds the framework in practice. HiLIFE is integrated with a distributed military simulation system, OTBSAF, and the RETSINA multi-agent infrastructure to provide agile and sophisticated reasoning. In addition, the paper presents validation results of the automated terrain analysis that were obtained through experiments using military intelligence Subject Matter Experts (SMEs). |
| Author | Sycara, Katia Grindle, LTC Charles Owens, Sean Glinton, Robin Yu, Bin Giampapa, Joseph Lewis, Michael |
| Author_xml | – sequence: 1 givenname: Katia surname: Sycara fullname: Sycara, Katia email: katia@cs.cmu.edu organization: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA – sequence: 2 givenname: Robin surname: Glinton fullname: Glinton, Robin organization: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA – sequence: 3 givenname: Bin surname: Yu fullname: Yu, Bin organization: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA – sequence: 4 givenname: Joseph surname: Giampapa fullname: Giampapa, Joseph organization: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA – sequence: 5 givenname: Sean surname: Owens fullname: Owens, Sean organization: School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA – sequence: 6 givenname: Michael surname: Lewis fullname: Lewis, Michael organization: School of Information Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA – sequence: 7 givenname: LTC Charles surname: Grindle fullname: Grindle, LTC Charles organization: School of Information Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA |
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