Barycentric coordinate-based distributed localization for wireless sensor networks subject to random lossy links - Wang, Ya; Shi, Lei; Chen, Xinming; Shao, Jinliang; Cheng, Yuhua; Wang, Houjun; Wang, Lijun (Neurocomputing (Amsterdam), 2023)
Distributed localization in wireless sensor networks is essential for verifying the positions of the sensor nodes deployed in the sensing field based on information interactions. However, the information transmitted from the controller to the actuator for each sensor node may be lost owing to communication noise, channel interference, or network congestion. With this in mind, this paper aims at investigating the distributed localization for wireless sensor networks subject to random lossy links. The barycentric coordinate, which can be determined by the distance measurements between node pairs in the network, is used as the basic scheme for range-based localization. First, based on the characterization of random link loss in wireless sensor networks with a Bernoulli random variable, a distributed iterative localization algorithm is proposed. And then, the global convergence of the proposed localization algorithm which ensures accurate localization is theoretically proved by using the convergence of sub-stochastic matrices’ product. Finally, numerical examples are conducted to illustrate the effectiveness of the proposed localization algorithm.