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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637483
• 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。特别感兴趣的是罕见或不寻常事件（离群值）的检测和分类。我们主要关注三种类型的传感器数据：（1）水下有线海洋观测网络中的水听器，（2）智能手机制作的任意麦克风阵列，（3）宽带无线电天线。我们方法的一个关键新奇是扩展我们早期成功的水听器数据，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，背景噪声和不必要的事件变得越来越复杂，风险也随之增加。该研究使用真实世界的测量数据，并通过与最终用户的互动进行指导。加拿大海洋网络公司在东北太平洋、不列颠哥伦比亚省维多利亚附近的萨利希海和北极地区设有几个电缆连接的海底观测站。这些观测站目前通过与海洋仪器相连的光纤电缆从海底连续提供真实的时间信息。水听器数据全天候传输并存档。这些数据中的大多数都是令人不感兴趣的噪音。挑战在于找到感兴趣的罕见（不寻常）音频事件，例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2.25亿美元的海底电缆观测站投资，以充分利用连续观测提供的机会。在大量数据中手动侦听、查找和分类罕见和不寻常的事件是不切实际的。所提出的罕见事件检测和分类算法是这些持续的海洋监测programmes.We认为麦克风阵列的任意和可能变化的几何形状，灵感来自无处不在的使用智能手机与GPS定位能力的成功是必不可少的。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和无线（收音机）以及麦克风，并且是可编程的。原则上，这些智能手机可以用于收集声学数据，这在人们（具有智能手机）聚集在一个地方（内部或外部）的情况下可能特别有趣。使用中的许多智能手机提供了产生大量数据的潜力。智能手机阵列的能力范围从估计源位置和/或房间特性（尺寸、材料反射系数）、去混响、声源分离、语音增强。这些功能可用于支持和增强对罕见事件的检测和分类，从而利用智能手机的无所不在来创建音频声音环境监测的新功能。超宽带（UWB）无线电系统已被广泛研究，并已商用。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范围内工作，但在低于约1 GHz时允许相同的频谱密度。在这个较低的范围内的UWB系统很少被研究。这个无线电频谱也有我们希望检测和分类的罕见事件（例如未经授权的传输，不寻常的传播现象）。这些UWB无线电系统可以被视为类似于音频系统，因为它们的带宽跨越超过10个倍频程，因此与水听器和智能手机一起使用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。