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An Energy Efficient Iterative Method for Source Localization in Wireless Sensor Networks

机译:无线传感器网络中源定位的能量高效迭代方法

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In this paper, we study the source localization problem in wireless sensor networks. Sensors transmit their quantized signal amplitude measurements to the fusion center and source location is estimated based on these quantized measurements. In this paper, we propose an energy efficient iterative localization scheme, where the algorithm starts with a coarse location estimate obtained from a set of anchor sensors. At each consecutive iteration, some of the non anchor sensors are activated which minimize the Posterior Cramer Rao Lower Bound (PCRLB). Then, using the available information received at previous iterations as side information, the quantized data of each activated sensor is further compressed to conserve energy using distributed data compression techniques prior to transmission to the fusion center. Simulation results show that the proposed iterative method achieves the same estimation performance as when all the sensors transmit their quantized data to the fusion center within a few iterations, while at the same time significantly reducing the communication requirements resulting in energy savings.
机译:在本文中,我们研究了无线传感器网络中的源定位问题。传感器将它们的量化信号幅度测量传输到融合中心,并且基于这些量化测量估计源位置。在本文中,我们提出了一种能量有效的迭代定位方案,其中算法从一组锚传感器获得的粗糙位置估计开始。在每个连续迭代时,一些非锚传感器被激活,最小化后克拉姆RAO下限(PCRLB)。然后,使用以前迭代处接收的可用信息作为侧信息,进一步被压缩了每个激活传感器的量化数据以在传输到融合中心之前使用分布式数据压缩技术来节省能量。仿真结果表明,该建议的迭代方法实现了与当所有传感器在几个迭代中传输到融合中心的融合中心时相同的估计性能,同时显着降低导致能量节省的通信要求。

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