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How to count targets given only the number of measurements

机译:仅在测量次数下如何计算目标

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摘要

The Bayes-optimal distribution of the number of targets is derived, given only the numbers of measurements in a sequence of K consecutive sensor scans. Target states and spatial properties of measurements are completely ignored. A backward recursion for the joint probability generating function of the target-measurement count is derived using a branching process model and independent causal influence assumptions. The counting model can be generalized to spatial branching processes.
机译:如果仅给出K个连续传感器扫描序列中的测量数量,则可以得出目标数量的贝叶斯最佳分布。测量的目标状态和空间属性被完全忽略。使用分支过程模型和独立的因果影响假设,得出目标测量次数联合概率生成函数的后向递归。计数模型可以推广到空间分支过程。

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