摘要 :
A joint probabilistic data association filter that uses adaptive update times for tracking targets in a cluttered environment is presented and compared with the joint probabilistic data association filter that uses a constant upda...
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A joint probabilistic data association filter that uses adaptive update times for tracking targets in a cluttered environment is presented and compared with the joint probabilistic data association filter that uses a constant update time. The tracking performance of the algorithm is assessed by Monte Carlo simulations on different target trajectories.
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