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Regularized Least Square Multi-Hops Localization Algorithm for Wireless Sensor Networks
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DOI：10.1109/ACCESS.2021.3116767.png)
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Abstract
En 中文
Position awareness is very important for many sensor network applications. However, the use of Global Positioning System receivers to every sensor node is very costly. Therefore, anchor based localization techniques are proposed. The lack of anchors in some Wireless Sensor Networks lead to the appearance of multi-hop localization, which permits to localize nodes even if they are far from anchors. One of the well-known multi-hop localization algorithms is the Distance Vector-Hop algorithm (DV-Hop). Although its simplicity, DV-Hop presents some deficiencies in terms of localization accuracy. Therefore, to deal with this issue, we propose in this paper an improvement of DV-Hop algorithm, called Regularized Least Square DV-Hop Localization Algorithm for multi-hop wireless sensors networks. The proposed solution improves the location accuracy of sensor nodes within their sensing field in both isotropic and anisotropic networks. We used the double Least Square localization method and the statistical filtering optimization strategy, which is the Regularized Least Square method. Simulation results prove that the proposed algorithm outperforms the original DV-Hop algorithm with up to 60%, as well as other related works, in terms of localization accuracy.
Keywords:
Location awareness
Wireless sensor networks
Estimation
Spread spectrum communication
Wireless communication
Reliability
Machine learning algorithms
Distance vector-hop algorithm
localization
localization accuracy
regularized least square
multi-hop wireless sensor networks
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
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