Parameter Estimation for Decoding Sensor Signals
Parameter Estimation for Decoding Sensor Signals
复制标题
解码传感器信号的参数估计
DOI：
10.1145/3576841.3589622
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Sprinkle, Jonathan
中科院分区：
文献类型：
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作者：
Nice, Matthew;Bunting, Matthew;Zachar, Gergely;Bhadani, Rahul;Ngo, Paul;Lee, Jonathan;Bayen, Alexandre;Work, Dan;Sprinkle, Jonathan
本文介绍了一种参数估计方法解码数字传感器信号的信息物理系统。对于未知或未完全表征的数字传感器数据，可能难以从背景或噪声中破译所需信号。在具有网络传感器的信息物理系统中，我们可以利用物理系统的知识来通知数字信号的解码。这项正在进行的工作是一个案例研究破译商用车车载传感器网络，通过控制器局域网（CAN）进行通信。通过了解库存车辆传感器网络，车辆可以扩展到一个可扩展的研究平台，最少的仪器。我们面临的挑战是定位所需的传感器信号编码的网络流量，包括其他传感器数据，控制消息，以及编码和安全开销。由于车辆的未知传感器网络，我们的方法开发的方法，有效地分析和识别关键信号，尽管潜在的信号嵌入的大的状态空间。这项工作的进展是一个正式的方法来破译相关的信号的非特征化的网络物理系统的贡献，在使用这种方法在车载传感器网络的案例研究。我们与用于分析数字信号的分析工具共享代码库。
This paper introduces a parameter estimation approach for decoding digital sensor signals in a cyber-physical system. For unknown or not fully characterized digital sensor data, it can be difficult to decipher a desired signal from background or noise. In a cyber-physical system with networked sensors, we can leverage knowledge of the physical system to inform the decoding of the digital signals. This work in progress is a case study on deciphering commercial vehicle on-board sensor networks that communicate through the Controller Area Network (CAN). By understanding the stock vehicle sensor network, a vehicle can be extended into a scalable research platform with minimal instrumentation. Our challenge was to localize desired sensor signals encoded in network traffic that included other sensor data, control messages, as well as encoding and security overhead. Due to the vehicle's unknown sensor network, our approach developed methods to efficiently analyze and identify key signals despite the large state-space for potential signal embeddings. The contribution of this work-in-progress is a formal approach to deciphering pertinent signals uncharacterized cyber-physical system, with a case study in using this approach in vehicle on-board sensor networks. We share a code repository with analysis tools for analyzing digital signals.
CANClassify：CAN 总线信号的自动解码和标记
DOI：
10.55708/js0110002
发表时间：
2022
期刊：
Journal of Engineering Research and Sciences
影响因子：
--
作者：
P. Ngo;J. Sprinkle;R. Bhadani
通讯作者：
R. Bhadani