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Rate-constrained target detection

机译：速率受限的目标检测

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摘要

Given little or no a priori information, a real world detection system has the task of allocating limited resources. Often these resources are themselves detection systems that operate at a slower rate, for example a tracker following a radar. Detection systems that are described by serial multiple decision points with each decision device assumed to be more reliable but slower than the device preceding it are considered. It is shown that because of the rate constraint the Neyman-Pearson criterion is suboptimum. An optimum rate-constraint test is developed which has the same likelihood ratio form as the Neyman-Pearson test. A strategy for controlling multiple-point detection sequences is developed that depends only on local information and is shown to be optimum under fairly broad conditions. The strategy can be implemented in practical systems, since it depends on the hit rate which is both controllable and observable. This approach to decision-making has applications in many fields and shows a promise as both an analysis and design tool.
机译：在很少或没有先验信息的情况下，现实世界的检测系统的任务是分配有限的资源。这些资源通常本身就是运行速度较慢的检测系统，例如跟踪雷达的跟踪器。考虑了通过串行多个决策点描述的检测系统，其中每个决策设备被认为比之前的设备更可靠，但速度较慢。结果表明，由于速率限制，Neyman-Pearson准则是次优的。开发了一种最佳速率约束检验，该检验具有与Neyman-Pearson检验相同的似然比形式。已开发出一种仅依赖于本地信息的控制多点检测序列的策略，并且在相当广泛的条件下显示出最佳的控制策略。该策略可以在实际系统中实施，因为它取决于可控和可观察的命中率。这种决策方法已在许多领域中得到应用，并有望作为分析和设计工具。

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