Evaluation of Data Association Hypotheses: Non-Poisson I.I.D. Cases

  title={Evaluation of Data Association Hypotheses: Non-Poisson I.I.D. Cases},
  author={Shozo Mori and Chee-Yee Chong},
This paper discusses evaluation of data association hypotheses for a general class of multiple target tracking problems. We assume that the number of targets is random and unknown, and given the number of targets, that the joint target state distribution forms a system of independent, identically distributed (i.i.d.) probability distributions. We are particularly interested in the cases in which the probability distribution of the number of targets is not necessarily Poisson. We will show that… CONTINUE READING
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