A multiple target tracking filter is developed for merged measurement problems that arise with finite resolution sensors. The resulting combinatorial problem is incorporated directly in the joint likelihood function using analytic combinatorics techniques. The Bayesian filter is a sum of several terms that correspond one-to-one to the set of all feasible hypotheses about measurements and targets, i.e., resolved/unresolved, detected/undetected. Performance is demonstrated for two targets in both crossing and parallel target motion scenarios.

中文翻译：

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未解决测量的多目标跟踪

针对由有限分辨率传感器引起的合并测量问题，开发了多目标跟踪滤波器。使用解析组合技术将所得组合问题直接合并到联合似然函数中。贝叶斯滤波器是与关于测量和目标的所有可行假设的集合一对一对应的几个项的总和，即，已解决/未解决，已检测/未检测到。在交叉和平行目标运动场景中，两个目标的性能都得到了证明。