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Source Localization in Wireless Sensor Networks From Signal Time-of-Arrival Measurements

机译:从信号到达时间测量中无线传感器网络中的源定位

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摘要

Recent advances in wireless sensor networks have led to renewed interests in the problem of source localization. Source localization has broad range of applications such as emergency rescue, asset inventory, and resource management. Among various measurement models, one important and practical source signal measurement is the received signal time of arrival (TOA) at a group of collaborative wireless sensors. Without time-stamp at the transmitter, in traditional approaches, these received TOA measurements are subtracted pairwise to form time-difference of arrival (TDOA) data for source localization, thereby leading to a 3-dB loss in signal-to-noise ratio (SNR). We take a different approach by directly applying the original measurement model without the subtraction preprocessing. We present two new methods that utilize semidefinite programming (SDP) relaxation for direct source localization. We further address the issue of robust estimation given measurement errors and inaccuracy in the locations of receiving sensors. Our results demonstrate some potential advantages of source localization based on the direct TOA data over time-difference preprocessing.
机译:无线传感器网络的最新进展引起了对源定位问题的新兴趣。源本地化具有广泛的应用程序,例如紧急救援,资产清单和资源管理。在各种测量模型中,一个重要且实用的源信号测量是一组协作无线传感器的接收信号到达时间(TOA)。在发射器上没有时间戳的情况下,在传统方法中,将这些接收到的TOA测量值成对减去以形成到达时间差(TDOA)数据以进行源定位,从而导致信噪比损失3 dB( SNR)。通过直接应用原始测量模型而无需进行减法预处理,我们采用了不同的方法。我们提出了两种利用半定编程(SDP)松弛进行直接源定位的新方法。考虑到测量误差和接收传感器位置的不准确性,我们进一步解决了鲁棒估计的问题。我们的结果证明了基于直接TOA数据的时域本地化相对于时差预处理的潜在优势。

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