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The conventional GMPHD/CPHD filters require the PHD for target births to be a Gaussian mixture (GM), which is potentially inefficient because careful selection of the mixture parameters may be required to ensure good performance. Here we present approximations which allow part of the birth PHD to be uniformly distributed, obviating the need to use a large GM to model target births. The benefits of this approach are demonstrated by simulations on a bearings-only filtering scenario.
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Beard et al. (2013) studied this question.
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