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Prediction-Based Localization for Mobile Wireless Sensor Networks

机译:移动无线传感器网络基于预测的本地化

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In this paper, we propose two extensions of SDPL (Speed and Direction Prediction-based Localization) method. The first is called MA-SDPL (Multiple Anchors SDPL) which uses multiple mobile anchors instead of only one. Each anchor has its own trajectory and its own departure point. The goal is to ensure a total coverage of the sensor field and to multiply the chance of receiving anchor beacons. Anchor Beacons help localizing mobile sensors. As a consequence, the location estimation will be enhanced. The second method deals with one mobile anchor but with the ability of multi-hoping, that is, when a sensor estimates that it is well enough localized, it sends beacons to its h-neighborhood about its current location, hence, it plays the role of an additional anchor. This solution reduces the cost comparing to when using multiple anchors and allows rapid location propagation. Simulation results show that the two extensions improve better the ratio of localized sensors and reduce the location error compared to the basic SDPL. We have also tested them in a noisy environment to be closer to a real deployment.
机译:在本文中,我们提出了SDPL方法的两个扩展(基于速度和方向预测的定位)。第一种称为MA-SDPL(多锚SDPL),它使用多个移动锚,而不是仅使用一个。每个锚点都有自己的轨迹和出发点。目的是确保传感器区域的总覆盖,并增加接收锚定信标的机会。锚定信标有助于定位移动传感器。结果,将增强位置估计。第二种方法处理一个移动锚,但具有多跳功能,即当传感器估计其定位足够好时,它将信标发送到其当前位置附近的h邻居,因此,它发挥了作用一个额外的锚点。与使用多个锚点相比,该解决方案降低了成本,并允许快速的位置传播。仿真结果表明,与基本的SDPL相比,这两个扩展可以更好地提高局部传感器的比例,并减少定位误差。我们还在嘈杂的环境中对它们进行了测试,以使其更接近实际部署。

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