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Network-centric multitarget tracking under communication constraints isconsidered, where dimension-reduced track estimates are exchanged. Previouswork on target tracking in this subfield has focused on fusion aspects only andderived optimal ways of reducing dimensionality based on fusion performance. Inthis work we propose a novel problem formalization where estimates are reducedbased on association performance. The problem is analyzed theoretically andproblem properties are derived. The theoretical analysis leads to anoptimization strategy that can be used to partly preserve association qualitywhen reducing the dimensionality of communicated estimates. The applicabilityof the suggested optimization strategy is demonstrated numerically in amultitarget scenario.

Track-To-Track Association for Fusion of Dimension-Reduced Estimates