Fitness Information Synchronization (FIS) Algorithm and Kalman Filter Based Under Water Target Localization

The localization of nodes in the underwater geographical condition is a vital part of Wireless Sensor Networks in the Water (UWSNs).UWSN helps in several ways oceanic explorations. The localization of nodes suffers a large imbalance due to uncertainty in oceanic conditions. So, this work focuses on enhancing the localization of nodes using fusion and Kalman filter. In this work, the fusion is done between two nodes' data which are the node's age of information and fitness factor nodes. The estimation is done using Fitness Information Synchronization (FIS) Algorithm. The localization process is tried to enhance by calculating the localization error between the actual and estimated position, and the deviation from the actual position. The simulation process is done on a MATLAB simulator. It is observed that the localization error decreases with the increase in time while the deviation from the actual position increases with time. Therefore, it is observed that there is a trade-off between these two constrained.