| Cramér-Rao lower bound for tracking multiple targets (2004) | |||||||||||
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| The derivation and computation of the theoretical Crame´r–Rao lower bounds for multiple target tracking has traditionally been considered to be a notoriously difficult problem. The authors present a simple and exact solution based on the assumption that raw sensor data (before thresholding) are available. The multi-target tracking problem can then be formulated as recursive Bayesian track-before-detect estimation. The advantage of this formulation is that it is identical to nonlinear filtering, for which the exact posterior Crame´r–Rao bound is already known. The paper presents several numerical examples in support of the theoretical findings. | |||||||||||
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