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Abstract
As one of the key techniques in wireless sensor networks (WSN), localization algorithm has been a research hot topic and indispensable function in most wireless applications. In order to promote localization accuracy and efficiency, a lot of localization algorithms with different performances and computation complexities have been proposed. The paper discusses the drawbacks of some typical works on localization, and proposes a hybrid localization algorithm integrated with approximate point in triangle (APIT) and distance vector-hop (DV-HOP). To address the positioning accuracy and coverage rate, the objectives of this paper are three folds: firstly, adopting angle detection to determine the exact direction of unknown nodes. Then, the APIT algorithm is adopted over all unknown nodes within the triangle and its localization error is reduced from 14.7215 m in conventional APIT to 3.2348 m in the considered scenario. Finally, the DV-HOP algorithm is adopted with different weights for the nodes within the minimum hops, and localizes the rest unknown nodes in WSN with localization accuracy increased by 49%.
Highlights
IntroductionHuge similar requirements of information sharing derive the development of the Internet of things
As we all know, huge similar requirements of information sharing derive the development of the Internet of things (IoT) gradually
If the unknown node is surrounded by the anchor nodes, the position of the triangle overlap region is estimated based on the approximate point in triangle (APIT) algorithm
Summary
Huge similar requirements of information sharing derive the development of the Internet of things. The second class of localization algorithms are designed without distance-information, such as APIT, DV-HOP, Centriod, Amorphous etc. In order to reduce localization errors of APIT, reference [5] proposes backtracking algorithm and method of regional detection. Reference [7] proposes a new method that can localize the whole region by using the least number of sensors. It cannot realize the localization of node itself. In [8], considering the impact of the distance of nodes on localization error, it modifies the traditional centroid algorithm by using the RSSI distance as weighting coefficients, and the localization accuracy is greatly improved.
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