首页> 外文会议>International Symposium on Automation and Robotics in Construction >SENSOR NETWORKS FOR ACOUSTIC SOURCE LOCALIZATION USING ACOUSTIC FINGERPRINT IN URBAN ENVIRONMENTS AND CONSTRUCTION SITES
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SENSOR NETWORKS FOR ACOUSTIC SOURCE LOCALIZATION USING ACOUSTIC FINGERPRINT IN URBAN ENVIRONMENTS AND CONSTRUCTION SITES

机译:使用城市环境和施工地点的声学指纹声学源定位传感器网络

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We investigate the feasibility and performance of the acoustic localization system using the acoustic fingerprint for asynchronous wireless sensor network (WSN) in urban environments and construction sites. The location estimation is calculated by comparing the acoustic fingerprint obtained from multiple sensors with those pre-computed in the database. To calculate the fingerprint, we avoid expensive measurement process by using a 2-dimensional finite-difference time-domain (FDTD) to approximate acoustic propagation in urban area. The implementation cost for constructing the acoustic fingerprint map using FDTD is small compared to that of the exhaustive data measurements over an entire test site. We select the direction-of-arrival (DoA) of the first arrival path of the acoustic signal as a location fingerprint to avoid complexity from synchronization. The fingerprint from each node is weighted by the measured amplitude of the received acoustic waveform to take into account the decrease in the amplitude due to the distance between the source and the sensor node. We test our proposed localization algorithm at the 140×80 m~2 artificial village area used for military drills. With proper node placement, our proposed algorithm can achieve strong localization performance using small number of sensor nodes. In particular, the root-mean-square-error (RMSE) between the estimated and accurate source position is 6.30 meters using observations from only 3 sensor nodes. Our proposed algorithm exhibits robustness to DoA estimation error representing the cumulative effect of uncertainties in urban environments and construction sites.
机译:我们研究了在城市环境和建筑工地中异步无线传感器网络(WSN)的声学指纹的声学定位系统的可行性和性能。通过将从多个传感器获得的声指纹与数据库预先计算的那些进行比较来计算位置估计。为了计算指纹,我们通过使用二维有限差分时间域(FDTD)来避免昂贵的测量过程,以近似城市区域的声学传播。使用FDTD构造声学指纹地图的实施成本与整个测试站点上的详尽数据测量相比,使用FDTD较小。我们选择声信号的第一个到达路径的到达方式(DOA)作为位置指纹,以避免同步复杂性。每个节点的指纹由所接收的声波形状的测量幅度加权,以考虑由于源极和传感器节点之间的距离导致的幅度的减小。我们在用于军事演习的140×80米〜2人工村区域测试我们提出的本地化算法。通过适当的节点放置,我们所提出的算法可以使用少量传感器节点来实现强大的本地化性能。特别地,估计和精确源位置之间的根均方误差(RMSE)使用仅3个传感器节点的观测值为6.30米。我们所提出的算法对DOA估计误差表现出具有代表城市环境和建筑工地不确定性的累积效果的鲁棒性。

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