Computational Framework for Target Tracking Information Fusion Problems

Tianyu Yang (), Jiongbai Liu (), Tasnim Ibn Faiz (), Chrysafis Vogiatzis () and Md. Noor-E-Alam ()
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Tianyu Yang: Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115
Jiongbai Liu: Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115
Tasnim Ibn Faiz: Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115
Chrysafis Vogiatzis: Industrial and Enterprise Systems Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
Md. Noor-E-Alam: Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts 02115

INFORMS Journal on Computing, 2025, vol. 37, issue 5, 1413-1432

Abstract: In this work, we propose computationally tractable techniques for extracting valuable information from diverse data sources collected by multiple sensors in a variety of formats (visual, sonar, quantitative, qualitative, social information, etc.). More specifically, we develop an integrated approach consisting of two algorithms for extracting information and achieving a consensus-based, robust solution. The first algorithm extracts solutions from sensors within each data source, whereas the second algorithm reaches a compromise among the generated solutions from the previous algorithm across all data sources. To accomplish these goals, we initially transform the multisensor multitarget tracking problem (MSMTT) problem into a multidimensional assignment problem. Subsequently, we introduce a decomposition-based multisensor recursive approach referred to as a revised multisensor recursive algorithm, which can efficiently deliver a robust solution for each single data source MSMTT problem. In the second algorithm, we extend our methodology to the multisource MSMTT problem by introducing a connection-based symmetric nonnegative matrix factorization technique, which is shown to be computationally feasible and efficient in obtaining high-quality solutions.

Keywords: multidimensional assignment problem; target tracking problem; information fusion; multisensor recursive algorithm; NMF decomposition (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:37:y:2025:i:5:p:1413-1432

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