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Particle filters would be the main other one I'd reach for. The ability to represent multiple hypotheses is a big advantage they have.


You can also construct multiple hypothesis trackers from multiple Kalman Filters, but there is a little more machinery. For example, Interacting Multiple Models (IMM) trackers may use Kalman Filters or Particle Filters, and a lot of the foundational work by Bar-Shalom and others focuses on Kalman Filters.




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