RIA: Distributed Signal Dectection in Uncertain Environments

RIA：不确定环境中的分布式信号检测

• 批准号: 9211298
• 负责人: Rick Blum
• 金额: $ 10.5万
• 依托单位: Lehigh University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1992
• 资助国家: 美国
• 起止时间: 1992-09-01 至 1996-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9211298&HistoricalAwards=false
• 关键词: RIA; Distributed; Signal; Dectection; Uncertain

Blum Distributing multiple sensors over some region for the purpose of detecting a signal in noise is becoming increasingly attractive. The majority of the research work concerning the design of such schemes has focused on signal detection problems where a complete observation model which categorizes the environment under consideration is known. This research deals with distributed detection schemes for cases where a complete observation model is not available due to incomplete knowledge of the operating environment. This is an extremely practical case which has applications in air traffic control, radar weather monitoring, and other radar and sonar systems. Robustness results for important cases with alternative hypothesis which are not simple, finite observation sample sizes, dependent observations, and non-additive observations are being sought. The plan to construct these schemes focuses on applying the theory of minimax robust statistics. Cases with nonstationary, possibly non- Gaussian background environments and possibly dependent observations are also being investigated.

Blum 为了检测噪声中的信号，在某个区域上分布多个传感器变得越来越有吸引力。大多数的研究工作都集中在信号检测问题，其中一个完整的观察模型，分类所考虑的环境是已知的。本研究涉及分布式检测方案的情况下，一个完整的观察模型是不可用的，由于不完整的知识的操作环境。这是一个非常实际的案例，在空中交通管制、雷达天气监测和其他雷达和声纳系统中有应用。正在寻求具有不简单的备择假设、有限观测样本量、相关观测和非加性观测的重要情况下的稳健性结果。构造这些方案的计划侧重于应用极小极大鲁棒统计理论。 非平稳的情况下，可能非高斯背景环境和可能相关的意见也正在调查.