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Seismic Detection Algorithm and Sensor Deployment Recommendations for Perimeter Security

机译:周边安全的地震检测算法和传感器部署建议

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Field studies were conducted in 2005 in Yuma, Arizona at the Yuma Proving Grounds (YPG) to document seismic signatures of walking humans. Walker-generated vertical ground vibrations were recorded using standard omnidirectional 4.5 Hz peak-resonance geophones. Walker position and speed were measured using portable GPS equipment. Collected seismic data were processed and hypothetical sensor performance predictions were made using an algorithm developed for the detection and classification of a walking intruder. Sample results for the Yuma study are presented in the form of sensor detection/classification vs. range plots, and color-coded animations of seismic sensor alarm annunciations during walking intruder tests. A perimeter intrusion scenario for a Forward Operating Base is defined that involves a walker approaching a sensor picket-line along a path exactly halfway between two adjacent sensors. This is considered a conservative representation of the perimeter intrusion problem. Summary plots derived from a binomial probability based analysis define intruder detection probabilities for different sensor spacings. For a 215 lb intruder walking in the Yuma test environment, a 90% probability of at least two walker-classified sensor detections is achieved at a sensor spacing of 140 m. Preliminary investigations show the intruder classification component of the discussed detection/classification algorithm to perform well at rejecting signals associated with a nearby idling vehicle and normal background noise.
机译:2005年在亚利桑那州的尤马市的尤马试验场(YPG)进行了实地研究,以记录行走中的人的地震信号。使用标准的全向4.5 Hz峰值共振地震检波器记录Walker产生的垂直地面振动。步行者的位置和速度是使用便携式GPS设备测量的。处理收集的地震数据,并使用开发用于步行入侵者的检测和分类的算法对传感器的性能进行预测。 Yuma研究的样本结果以传感器检测/分类与距离图的关系以及步行入侵者测试期间地震传感器报警信号的彩色编码动画的形式呈现。定义了“前向作战基地”的周边入侵场景,其中涉及步行者沿着两个相邻传感器之间正好一半的路径接近传感器纠察线。这被认为是外围入侵问题的保守表示。从基于二项式概率的分析得出的摘要图定义了不同传感器间距的入侵者检测概率。对于在Yuma测试环境中行走的215 lb的入侵者,在140 m的传感器间距处至少有90%的概率进行了两次沃克分类传感器的检测。初步调查显示,所讨论的检测/分类算法的入侵者分类组件在拒绝与附近空转的车辆和正常背景噪声相关的信号时表现良好。

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