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In problems with large number of measurements from objects located in a dense environment, identifying which measurement came from which target becomes pertinent. To do so in a real-time scenario requires curtailing the growing number of hypotheses generated. This work proposes one such way to reduce the number of hypotheses by handling data differently.

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This page is a summary of: Tensor Decomposition Approach to Data Association for Multitarget Tracking, Journal of Guidance Control and Dynamics, September 2019, American Institute of Aeronautics and Astronautics (AIAA),
DOI: 10.2514/1.g004122.
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