基于改进遗传算法的多波束水下地形匹配方法

Multi-beam underwater terrain matching method based on improved genetic algorithm

传统地形匹配算法在初始位置误差较大的条件下,由于搜索区域过大,定位精度较低,容易发生误匹配。针对此问题,提出一种基于改进遗传算法(GA)的多波束水下地形匹配方法。首先,根据地形变化特征,在多波束测深数据中自适应选择多条水深数据作为匹配序列,提高在地形相似处的匹配精度;然后,设计适应度函数用于衡量匹配航迹与真实航迹的相似度,加入收敛因子以减小惯导累积误差的影响;最后,利用正余弦算法对遗传算法进行优化,提高算法收敛速度,改善局部收敛的问题。仿真与船载实验结果表明,基于改进GA的多波束匹配方法对初始位置误差的大小不敏感,在分辨率为1 m的地形图上,匹配定位误差小于3 m,相比ICCP方法,在不同初始位置误差的情况下,定位精度分别提高了53%和79%。

Under the condition of large initial position error,the traditional terrain matching algorithm has low positioning precision and is prone to false matching due to the large search area.To solve the problem,a multi-beam underwater terrain matching method based on improved genetic algorithm is proposed.Firstly,according to the characteristics of terrain changes,multiple water depth data are adaptively selected from multibeam bathymetric data as the matching sequence to improve the matching precision in similar terrain;Then,a fitness function is designed to measure the similarity between the matched track and the real track,and a convergence factor is added to reduce the influence of the accumulated error of the inertial navigation;Finally,the sine cosine algorithm is used to optimize the genetic algorithm to improve the convergence speed and the performance of local convergence.Simulation and shipborne experiments show that the multi-beam matching method based on improved GA is insensitive to the initial position error,and the matching positioning error is less than 3m on the topographic map with a resolution of 1 m.Compared with the ICCP method,the positioning accuracy of the proposed method is improved by 53%and 79%respectively under different initial position errors.