A Node Selection Algorithm Based on Multi-Objective Optimization Under Position Floating

Almost all existing node selection algorithms of the underwater sensor networks (USNs) are designed by assuming ideal environments. However, position floating nodes which caused ocean currents cannot be ignored in practice. Aiming at solving this problem during target tracking, a algorithm based on multi-objective optimization under was proposed paper. First, error is converted into noise. Then, as criteria for selection, both Fisher information matrix (FIM) and mutual (MI) derived particle filter (PF-PF). Finally, number nodes, corresponding FIM MI set objective function, nondominated sorting genetic II (NSGA-II) Technique Order Preference Similarity to Ideal Solution (TOPSIS) used find optimal scheme. Simulation results show that can overcome influence floating, ultimately, its tracking performance more stable accurate.