Adaptive virtual anchor node based underwater localization using improved shortest path algorithm and particle swarm optimization (PSO) technique

Detection and accurate position estimation have become an essential task for any static underwater acoustic sensor networks. Many localization schemes have been introduced in the field of terrestrial WSN over the last few decades. These schemes are still not perfectly realizable in a harsh underwater environment due to their erroneous communication channel and infrastructure-less environment. Limited localization coverage, propagation error, and accuracy are the major drawbacks in acoustic communication. This article proposed an adaptive virtual anchor node based on the improved shortest path algorithm with PSO technique. The main advantages of this proposed scheme are divided into two parts. First, introducing an enhanced shortest path algorithm can reduce the propagation error generated through multi-hop zigzag movement and improve the coverage. Second, the particle swarm optimization algorithm with virtual anchor nodes can significantly enhance the accuracy by reducing the errors to localize the unknown nodes. Investigational results manifest that the proposed methodology performed better than the Improved DV-Hop +PSO, IRL-WOA, and basic DV-Hop methods as far as their restriction. The proposed method improved 23%, 30%, and 35% better localization error, 10%, 15%, and 22% better relative localization error, and 10%, 18%, and 25% better accuracy respectively.