Prediction and positioning of UWSN mobile nodes based on tidal motion model

As the node positioning of underwater wireless sensor networks is easily affected by tidal motion, ocean current motion and multipath effect, the node positioning accuracy is low. In order to better improve the positioning accuracy of moving nodes of underwater wireless sensor networks, a method of locating mobile nodes of underwater wireless sensor based on tidal motion model is proposed. Firstly, the Time Difference of Arrival (TDOA) localization optimized by niche genetic algorithm is used to initialize each node. The integration of niche technology can effectively find multiple excellent solutions in the solution space, thus providing more abundant solution choices. This algorithm has excellent performance in multi-modal optimization problems, and can avoid the algorithm falling into local optimal solutions, so as to obtain more comprehensive optimization results. The simulation results show that the proposed algorithm has better positioning accuracy than the traditional Chan algorithm and Taylor algorithm. Then, each node is updated in real time by the optimized tidal movement model formula predicted by Kalman filter algorithm. The prediction algorithm is used to compare the real-time predicted update position of the node with the actual position. The positioning distance error of the prediction algorithm is also enough to meet the practical application requirements.