Broadband sensor signal processing, detection and classification of rare and unusual events

宽带传感器信号处理、罕见和异常事件的检测和分类

• 批准号: RGPIN-2014-06644
• 负责人: Driessen, Peter
• 金额: $ 1.82万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=649598
• 关键词: Broadband; sensor; signal; processing; detection

The research program is the area of extracting information from broadband sensors and arrays, both acoustic and electromagnetic. Of particular interest is the detection and classification of rare or unusual events (outliers). We focus on data from three types of sensors: (1) hydrophones in underwater cabled ocean observatory networks, (2) arbitrary microphone arrays made with smartphones, and (3) broadband radio antennas.**A key novelty of our approach is to expand upon on our early success with hydrophone data to include other sensor types, and exploring the application of audio signal processing techniques to broadband radio signals. The background noise and unwanted events become increasingly complex as we move from hydrophones to smartphones to radio, with associated increase in risk. The research uses real-world measured data and is guided by interaction with end users. Applications range from sound environment monitoring to marine biology to wireless communications to security.**Ocean Networks Canada operates several cable-linked seafloor observatories in the Northeast Pacific Ocean, Salish Sea near Victoria BC and the Arctic. These observatories currently deliver continuous real time information from the seafloor via fibre optic cables connected to oceanographic instruments. Hydrophone data is streamed 24/7 and archived. Most of this data is uninteresting noise. The challenge is to find the rare (unusual) audio events of interest such as shipping and marine mammal activity. The work leverages the $225M investment in Ocean Networks Canada cabled undersea observatories, to fully exploiting the opportunity provided by continuous observation. It is impractical to manually listen, find and classify rare and unusual events in the huge volume of data. The proposed rare event detection and classification algorithms are essential for the success of these sustained ocean monitoring programs.**We consider microphone arrays of arbitrary and possibly changing geometry, inspired by the ubiquitous use of smart cellphones with GPS location abilities. Smartphones are a promising platform for experimentation since they include speakers and wireless (radios) as well as microphones and are programmable. In principle, these smart cellphones may be used to gather acoustic data, which may be particularly interesting where people (with smartphones) are gathered in one place (inside or outside). The many smartphones in use offer the potential to generate a huge volume of data. Smartphone array capabilities range from estimating source locations and/or room characteristics (dimensions, material reflection coefficients), de-reverberation, sound source separation, speech enhancement. These capabilities can be used to support and enhance the detection and classification of rare events, thus using the omnipresence of smartphones to create new capabilities in audio sound environment monitoring.**Ultra-wideband (UWB) radio systems have been studied extensively and are commercially available. The regulations in the US specify the maximum spectral density (power per unit bandwidth). Most UWB equipment operates in the 3-10 GHz range but the same spectral density is permitted below about 1 GHz. UWB systems in this lower range are much less commonly studied. This radio spectrum also has rare events of interest (e.g. unauthorized transmissions, unusual propagation phenomena) that we wish to detect and classify. These UWB radio systems may be viewed as analogous to audio systems in that their bandwidth spans more than 10 octaves, thus the techniques for rare event detection used with hydrophones and smartphones may be adapted for radio. Applications include wireless communications, infrastructure monitoring and surveillance.

该研究计划是从宽带传感器和阵列中提取信息的领域，包括声学和电磁。特别令人感兴趣的是对罕见或不寻常事件(离群值)的检测和分类。我们关注来自三种传感器的数据：(1)水下电缆海洋观测站网络中的水听器，(2)用智能手机制作的任意麦克风阵列，以及(3)宽带无线电天线。**我们方法的一个关键创新是在我们早期成功的水听器数据的基础上扩展到包括其他类型的传感器，并探索音频信号处理技术在宽带无线电信号中的应用。随着我们从水听器到智能手机再到无线电，背景噪音和不想要的事件变得越来越复杂，风险也随之增加。这项研究使用了真实世界的测量数据，并以与最终用户的互动为指导。应用范围从声音环境监测到海洋生物，再到无线通信和安全。**加拿大海洋网络公司在东北太平洋、公元前维多利亚附近的萨利什海和北极地区经营着几个电缆连接的海底观测站。这些观测站目前通过连接到海洋仪器的光纤电缆提供来自海底的连续实时信息。水听器数据全天候流传输并存档。这些数据中的大部分都是乏味的噪音。挑战是找到人们感兴趣的罕见(不寻常)音频事件，如航运和海洋哺乳动物活动。这项工作利用了加拿大海洋网络公司2.25亿美元的投资，为海底观测站铺设了电缆，以充分利用持续观测提供的机会。在海量数据中人工监听、发现和分类稀有和不寻常的事件是不切实际的。提出的罕见事件检测和分类算法对于这些持续的海洋监测项目的成功至关重要。**我们考虑了任意和可能变化的几何形状的麦克风阵列，灵感来自于普遍使用的具有GPS定位功能的智能手机。智能手机是一个很有前途的实验平台，因为它们包括扬声器、无线(无线电)和麦克风，并且是可编程的。原则上，这些智能手机可以用来收集声学数据，当人们(带着智能手机)聚集在一个地方(室内或室外)时，这可能特别有趣。正在使用的许多智能手机提供了产生海量数据的潜力。智能手机阵列的功能范围从估计信号源位置和/或房间特征(尺寸、材料反射系数)、去混响、声源分离、语音增强。这些能力可用于支持和增强罕见事件的检测和分类，从而利用智能手机的无处不在来创建音频声音环境监测的新能力。**超宽带(UWB)无线电系统已得到广泛研究，并已投入商业使用。美国的法规规定了最大频谱密度(每单位带宽的功率)。大多数UWB设备在3-10 GHz范围内运行，但在大约1 GHz以下允许相同的频谱密度。在这个较低范围内的超宽带系统的研究要少得多。此无线电频谱还包含我们希望检测和分类的罕见事件(例如，未经授权的传输、异常传播现象)。这些UWB无线电系统可以被视为类似于音频系统，因为它们的带宽跨度超过10个八度，因此用于水听器和智能手机的罕见事件检测技术可以适用于无线电。应用包括无线通信、基础设施监控和监视。