ATD: Statistical Methods for Nuclear Material Surveillance Using Mobile Sensors

ATD：使用移动传感器进行核材料监测的统计方法

• 批准号: 0915139
• 负责人: Minge Xie
• 金额: $ 37.39万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915139&HistoricalAwards=false
• 关键词: ATD; Statistical; Methods; Nuclear; Material

The research in this proposal outlines a robust system of a mobile sensor network and develops statistical algorithms and models to provide consistent, pervasive and dynamic surveillance for nuclear or biological materials in major cities. Specifically, the project proposes a novel design of sensor network, in which nuclear sensors and Global Position System (GPS) tracking devices are installed on a large number of vehicles such as taxicabs and police vehicles. Real time information from this network is processed at a central surveillance center, where mathematical and statistical analyses are performed. The proposed statistical approaches include multiple spatial cluster detection method using latent models and state-space model for real-time detection and tracking of possibly moving nuclear sources using sequential Monte Carlo method. The methods are general and flexible and can be used in other settings involving a massive network of sensors. Threats to national and homeland security have become more dynamic and complex in the past decade due to global terrorism, increased opposition to U.S. interests, and increased access by adversaries to sophisticated technologies and materials. Among the threats, nuclear attacks is one of the most devastating acts, with severe losses of human lives as well as long term and large scale damages to infrastructures. As a result, there have been growing concerns regarding the prospect of detonating nuclear materials or dirty bombs in the populous metropolitan areas. It becomes more and more vital to have sophisticated nuclear surveillance and detection systems deployed in major cities in the U.S. to protect infrastructures and human lives. The proposed research on surveillance systems of a mobile sensor network can have broad impacts in advancing our detection capabilities of terrorist threats hence improving homeland security. During the course of the proposed project, activities related to education and training of graduate and undergraduate students will be actively engaged, in preparation for their possible careers in this area.

该提案的研究概述了一个强大的移动的传感器网络系统，并开发了统计算法和模型，以便对主要城市的核材料或生物材料进行一致、普遍和动态的监测。具体而言，该项目提出了一种新颖的传感器网络设计，其中核传感器和全球定位系统（GPS）跟踪设备安装在大量车辆上，如出租车和警车。 来自该网络的真实的实时信息在中央监控中心进行处理，在那里进行数学和统计分析。提出的统计方法包括使用潜在模型的多空间簇检测方法和使用顺序蒙特卡罗方法实时检测和跟踪可能移动的核源的状态空间模型。 该方法是通用的和灵活的，可以用于其他设置涉及一个庞大的传感器网络。 在过去十年中，由于全球恐怖主义、反对美国利益的势力增加以及对手获得尖端技术和材料的机会增加，对国家和国土安全的威胁变得更加动态和复杂。在这些威胁中，核攻击是最具破坏性的行为之一，造成严重的生命损失以及对基础设施的长期和大规模破坏。 因此，人们越来越担心在人口稠密的大都市地区引爆核材料或脏弹的前景。 在美国主要城市部署先进的核监视和探测系统以保护基础设施和人类生命变得越来越重要。拟议中的移动的传感器网络的监视系统的研究可以在提高我们的恐怖威胁的检测能力，从而提高国土安全的广泛影响。在拟议的项目实施过程中，将积极开展与研究生和本科生教育和培训有关的活动，为他们在这一领域可能从事的职业做准备。