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Optimizing over a variant of the Mean Optimal Subpattern Assignment (MOSPA) metric is equivalent to optimizing over the track accuracy statistic often used in target tracking benchmarks. Past work has shown how obtaining a Minimum MOSPA (MMOSPA) estimate for target locations from a Probability Density Function (PDF) outperforms more traditional methods (e.g. maximum likelihood (ML) or Minimum Mean...
Minimum mean squared error estimates generally are not optimal in terms of a common track error statistic used in tracking benchmarks, namely a form of the Mean Optimal Sub-pattern Assignment (MOSPA) metric. We derive an explicit solution for the MOSPA-optimal estimates for two scalar targets. We also generalize previous work on permutation variant and invariant PDF decompositions by Blom and Bloem...
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