首页> 外文会议>Conference on unattended ground, sea and air sensor technologies and applications XI; 20090413-16; Orlando, FL(US) >A Data-driven Personnel Detection Scheme for Indoor Surveillance using Seismic Sensors
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A Data-driven Personnel Detection Scheme for Indoor Surveillance using Seismic Sensors

机译:基于地震传感器的室内监视数据驱动人员检测方案

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This paper describes experiments and analysis of seismic signals in addressing the problem of personnel detection for indoor surveillance. Data was collected using geophones to detect footsteps from walking and running in indoor environments such as hallways. Our analysis of the data shows the significant presence of nonlinearity, when tested using the surrogate data, method. This necessitates the need for novel detector designs that are not based on linearity assumptions. We present one such method based on empirical mode decomposition (EMD) and functional data analysis (FDA) and evaluate its applicability on our collected dataset.
机译:本文介绍了地震信号的实验和分析,以解决室内监视人员检测的问题。使用地震检波器收集数据,以检测室内环境(如走廊)中行走和跑步的脚步声。当使用替代数据方法进行测试时,我们对数据的分析显示出非线性的显着存在。这就需要不基于线性假设的新颖检测器设计。我们提出一种基于经验模式分解(EMD)和功能数据分析(FDA)的方法,并评估其在我们收集的数据集上的适用性。

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