An Intellectual Method for Range-free Localization in Underwater Acoustic Sensor Networks

In this article the localization in underwater Acoustic Sensor Networks is studied. Unlike earth networks, the global positioning system does not work under sea environment. Limited bandwidth, multidirectional channel and the cost of submarine props all make the localization a challenging problem. On the other hand, range-based localization algorithms are not suitable for underwater networks. In this paper an intellectual and optimized range-free localization method using of neural network is introduced. First DV-hop schema is simulated that is a range-free schema. Its drawback is to be less accurate due to its accuracy depends on distance determination. Then optimized method is presented that is based on range-free schema. In this method, average distance between sensor node and connected anchor nodes, position of anchor nodes are given to a neural network. This neural network determinates position of sensor nodes after training. Simulation results shows that this new method clarifies the node position and is highly accurate. This method has very low fault in comparison with DV-hop and is inexpensive regarding the costs and does not need explicit concurrency of the nodes. Also the network coverage is good.