粒子群优化算法在海底地形导航中的应用

Application of particle swarm optimization algorithm in the seabed terrain navigation

通过研究将连续粒子群优化算法离散化,提出二进制离散粒子群优化算法。在海底地形导航的非线性、实时性、精准性的情况下,利用2个子群的协同进化来降低陷入局部最优的风险,有效提高收敛速度。最后通过与传统的地形轮廓匹配算法进行对比,说明本文算法在经纬度误差和最佳匹配点定位方面更具优越性。

This paper studied the discrete continuous particle swarm optimization algorithm. A binary discrete particle swarm optimization algorithm was proposed. And in the case of the nonlinear,real-time and accuracy of the seabed terrain navigation,use the co evolution of two subgroups to reduce the risk of falling into local optimum. Effectively improve the convergence rate. In the end,the algorithm was more superior to the best matching point positioning by comparing with the traditional terrain contour matching algorithm.