论文标题
传感器网络上的分布异常检测和估计：观察等值和Q冗余观察者设计
Distributed Anomaly Detection and Estimation over Sensor Networks: Observational-Equivalence and Q-Redundant Observer Design
论文作者
论文摘要
在本文中，我们通过传感器网络的分布式估计来研究无状态和状态的基于物理的异常检测方案。在状态情况下，检测器会跟踪传感器残差（即估计和真实输出的差异），并报告警报，如果记录的残差的某些统计数据偏离了预定义的阈值，例如χ^2（Chi-Square）检测器。取而代之的是，只有残差的瞬时偏差才能在无状态情况下引起警报，而无需考虑传感器输出和估计数据的历史记录。给定（大约）两种情况下的假警报率，我们提出了基于噪声统计数据的概率阈值设计。我们通过模拟显示，在状态情况下增加窗口长度可能不一定会降低虚假警报率。另一方面，它增加了不需要的延迟以提高警报。所提出的检测算法的分布式方面通过添加冗余的观察性传感器，可以通过可能的恢复解决方案将故障传感器局部隔离。然后，我们为设计Q冗余的分布式观察者提供了一种机制，对网络上的Q传感器的故障（或删除）稳健。
In this paper, we study stateless and stateful physics-based anomaly detection scenarios via distributed estimation over sensor networks. In the stateful case, the detector keeps track of the sensor residuals (i.e., the difference of estimated and true outputs) and reports an alarm if certain statistics of the recorded residuals deviate over a predefined threshold, e.g., χ^2 (Chi-square) detector. Instead, only instantaneous deviation of the residuals raises the alarm in the stateless case without considering the history of the sensor outputs and estimation data. Given (approximate) false-alarm rate for both cases, we propose a probabilistic threshold design based on the noise statistics. We show by simulation that increasing the window length in the stateful case may not necessarily reduce the false-alarm rate. On the other hand, it adds unwanted delay to raise the alarm. The distributed aspect of the proposed detection algorithm enables local isolation of the faulty sensors with possible recovery solutions by adding redundant observationally-equivalent sensors. We, then, offer a mechanism to design Q-redundant distributed observers, robust to failure (or removal) of up to Q sensors over the network.
