Reach质心定位算法

Adeniran Ademuwagun, Verdicchio Fabio
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引用次数: 16

摘要

尽管准确或精确的位置估计总是可取的,但由于传感器节点定位而产生的粗精度通常就足够了。为了达到这样的精度水平,人们正在探索无距离定位技术,作为基于距离定位技术的低成本替代品。为了管理成本,在无线传感器环境中部署了几个位置感知节点,称为锚点。通过这些锚点,所有其他自由节点都可以估计自己的位置。因此,本文将着眼于一些最重要的无距离定位算法,详细说明它们的局限性,并提出一种改进形式的质心定位算法,称为到达质心定位算法。该算法通过观察接收信号强度质量的一致性,采用一种锚节点位置验证机制。在自由节点附近的每个锚都会使用接收到的信号强度来验证其附近其他锚的实际位置或邻近程度。这一过程减轻了无线电波的多径效应,特别是在封闭环境中,从而限制了定位估计误差和不确定性。然后使用质心定位算法通过验证机制选择锚点来估计节点的位置。我们的定位方法变得更加重要,特别是在室内环境中,无线电信号特征不一致或完全不可靠。仿真结果表明,与原质心定位算法、近似三角点定位算法和DV-Hop算法相比,该算法的定位精度有了显著提高。
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Reach Centroid Localization Algorithm
As much as accurate or precise position estimation is always desirable, coarse accuracy due to sensor node localization is often sufficient. For such level of accuracy, Range-free localization techniques are being explored as low cost alternatives to range based localization techniques. To manage cost, few location aware nodes, called anchors are deployed in the wireless sensor environment. It is from these anchors that all other free nodes are expected to estimate their own positions. This paper therefore, takes a look at some of the foremost Range-free localization algorithms, detailing their limitations, with a view to proposing a modified form of Centroid Localization Algorithm called Reach Centroid Localization Algorithm. The algorithm employs a form of anchor nodes position validation mechanism by looking at the consistency in the quality of Received Signal Strength. Each anchor within the vicinity of a free node seeks to validate the actual position or proximity of other anchors within its vicinity using received signal strength. This process mitigates multipath effects of radio waves, particularly in an enclosed environment, and consequently limits localization estimation errors and uncertainties. Centroid Localization Algorithm is then used to estimate the location of a node using the anchors selected through the validation mechanism. Our approach to localization becomes more significant, particularly in indoor environments, where radio signal signatures are inconsistent or outrightly unreliable. Simulated results show a significant improvement in localization accuracy when compared with the original Centroid Localization Algorithm, Approximate Point in Triangulation and DV-Hop.
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