Sequential multiple target detection using particle filters
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We create and compare three sequential hypothesis tests for multiple target detection using particle filters. The algorithm with best performance assigns a variable number of particles to each hypothesis according to the posterior probabilities to optimise computational resources. Besides, the posterior probabilities of the hypotheses are calculated in a robust way regarding sample degeneracy. © 2011 IEEE.