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On the use of least favorable distributions to facilitate the design of randomly deployed sensor detection systems.

机译:使用最不利的分布来促进随机部署的传感器检测系统的设计。

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摘要

Sensor detection systems with a fusion center are being considered to detect a low-power signal emitter in an unknown location within a region of interest. For example, multiple radiation sensors can be distributed in a region to detect the presence of an unauthorized radioactive material. When designing such a system, the designer faces the problem that the measurements are conditionally dependent in general. Designs for conditionally dependent measurements are significantly more difficult to achieve than designs for conditionally independent measurements. Furthermore, the distribution of measurements depends on variables with unknown distributions, such as the emitter location, which means that the alternative hypothesis is composite. Although it is possible to use the theory of least favorable distributions to deal with a composite hypothesis, many of the results in this theory require conditionally independent measurements. If the designer assumes that measurements are conditionally independent, then any performance analysis may be invalid because such an assumption is generally considered unrealistic and only justified by convenience.;How can the designer deal with the difficulties associated with conditionally dependent measurements and the composite hypothesis? It is shown in this dissertation that there are conditions that allow a designer to deal with these problems by assuming a least favorable distribution for the emitter location that not only makes the hypothesis simple and ensures detection performance, but also causes the measurements to become conditionally independent and identically distributed. It is shown that under certain conditions, any distribution that places the emitter on a subset of the boundary of the region of interest with probability one is least favorable for various systems of interest. This result may be considered intuitive; however, it does not hold in general.;Since a design based on a least favorable distribution may be considered too conservative, this dissertation proposes the use of a most favorable distribution for the emitter location and uses the theory of asymptotic relative efficiency (ARE) to evaluate how conservative the design based on a least favorable distribution is. The ARE theory is further used to, under a least favorable distribution, compare different systems and different sensor deployment strategies.
机译:具有融合中心的传感器检测系统被认为可以检测感兴趣区域内未知位置的低功率信号发射器。例如,多个辐射传感器可以分布在一个区域中以检测未经授权的放射性材料的存在。在设计这样的系统时,设计人员面临的问题是,测量通常是有条件的。与条件独立测量相比,用于条件依赖测量的设计要难得多。此外,测量的分布取决于具有未知分布的变量,例如发射器的位置,这意味着备选假设是复合的。尽管可以使用最不利分布的理论来处理复合假设,但该理论中的许多结果都需要有条件地进行独立测量。如果设计人员假设测量是有条件独立的,那么任何性能分析都可能是无效的,因为这样的假设通常被认为是不现实的,只有通过方便才能证明其合理性;设计人员如何处理与条件相关的测量和综合假设相关的困难?本论文表明,存在一些条件可以使设计人员通过假设发射器位置的最不利分布来处理这些问题,这不仅使假设变得简单并确保了检测性能,而且使测量变得有条件地独立。并且分布均匀。结果表明,在某些条件下,任何以概率一将发射器置于感兴趣区域边界的子集上的分布,对于各种感兴趣的系统都是最不利的。该结果可以被认为是直观的。由于基于最小有利分布的设计可能被认为过于保守,因此本文提出了对发射极位置使用最有利的分布,并使用渐近相对效率(ARE)理论评估基于最不利分布的设计的保守程度。 ARE理论进一步用于在最不利的分布下比较不同的系统和不同的传感器部署策略。

著录项

  • 作者单位

    The University of Wisconsin - Madison.;

  • 授予单位 The University of Wisconsin - Madison.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 188 p.
  • 总页数 188
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:43:41

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