【摘要】 为了实现在已知的地磁场区域内快速、智能化地选取易于实现地磁匹配的适配区,提高地磁匹配概率,给出了一种基于免疫粒子群优化算法的地磁特征区域选择方法。将地磁特征区域选择视为一个组合优化问题,通过一定的粒子编码和搜索策略,在规则网格化的地磁图中实现一定大小的、空间连续分布的特征区域选择。采用MSD匹配算法在不同路径的各种噪声强度下进行匹配仿真,实验结果表明,在所选择的适配区内,地磁匹配概率远高于整个地磁场区的平均匹配概率,特别是随着噪声强度的增加这种优势愈发明显。更多还原

【Abstract】 An immune PSO (Particle Swarm Optimization) algorithm-based intelligent selective method is proposed to improve the success rate of geomagnetic matching in a certain geomagnetic area.The characteristic area selection is taken as an integrated optimization technigue.Some characteristic areas of certain size and continuous distribution in the regular grids of geomagnetic map are selected according to a certain particle code and search strategy.A mean square deviation (MSD) matching algorithm is adopted to simulate the matching probability under different noise situations and routes.The simulation results show that the probability of geomagnetic matching in selective areas is higher than the average value of the whole geomagnetic field,especially with noise intensity increasing.更多还原