Optimization of warship degaussing decision based on poly-population particle swarm algorithm

In order to disguise and hide themselves better, warships and submarines are equipped with degaussing windings. But, with the development of warship degaussing technology, more and more degaussing coils are being adopted. Thus, conventional methods for calibrating the degaussing system are increasingly difficult to implement. Combining incomplete evolution of every particle swarm and the idea of compressing the space, the evolution of LDW-PSO and space compression is done alternately, until the global optimization solution is got. Through the incomplete evolution of LDW-PSO algorithm, adequate preferable information is got to provide the foundation to reduce the searching space; the collective decision-making of the elite particle group is used to decide the scope of the new space. Taking some warship as an example, the proposed method was applied to adjust the degaussing system and the optimized calibrating mathematical model and optimization results are given. Simulation results are presented, which shows that this algorithm is advantageous to others, in terms of minimizing the vessel degaussing magnetic signature RMS value and peak value, and that this method can be used to optimize one parameter or combinational parameters that relate to the vessel or submarine´s magnetic signature, so the vessel or submarine degaussing system is calibrated to an optimal state, and the vessel or submarine´s magnetic safety is ensured. Furthermore, this optimization algorithm has many advantages, such as intuitional algorithm, simple programming, high calculating speed, which makes easy collaborating multi-computer and applying it to real project.