An Adaline-Based Location Algorithm for Wireless Sensor Network

Authors:
Fengjun Shang
Affiliations:
College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China 400065
Venue:
ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
Year:
2009

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Abstract

Localization is used in location-aware applications such as navigation, autonomous robotic movement, and asset tracking to position a moving object on a coordinate system. In this paper, we present an improved DV-Hop algorithm based on Adaline(adaptive linear neuron) and DV-Hop, called ADV-Hop. The algorithm makes three major contributions to the localization problem in the wireless sensor networks(WSNs). First, we present a practical, fast and easy-to-use localization scheme with relatively high accuracy and low cost for WSNs. Second, the proposed algorithm improves location accuracy than the DV-Hop algorithm. Third, we explored the influence of anchor nodes on localization performance of the ADV-Hop algorithm. The proposed method can improve location accuracy and coverage without increasing hardware cost of sensor node. Simulation results show that the performance of this algorithm is superior to the original DV-Hop algorithm. Compared with DV-Hop, it is more available for WSNs.