基于自适应粒子群优化的地形匹配方法  

Terrain Matching Method Based on Adaptive Particle Swarm Optimization

作　　者：缪珅伟 何梓君 李荣冰[1] MIAO Shenwei;HE Zijun;LI Rongbing(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 211106;The Fourth Military Representative Office of the Air Force Equipment Department in Nanjing,Nanjing 210012)

机构地区：[1]南京航空航天大学自动化学院,南京211106 [2]空装驻南京地区第四军事代表室,南京210012

出　　处：《导航与控制》2025年第1期42-52,共11页Navigation and Control

基　　金：十四五预研项目(编号:30105010301)。

摘　　要：争夺低空复杂环境下的控制权对现代作战具有重要意义,地形辅助导航是实现低空环境下导航定位的有效手段。为解决传统批处理地形匹配算法实时性差和对地形起伏敏感的问题,提出了一种基于自适应粒子群优化的地形匹配方法。在搜索匹配阶段,采用粒子群优化算法代替传统的遍历寻优,利用序贯相似性检测构建相关性计算模型并将其作为粒子的适应度,在搜索迭代过程中,根据粒子适应度的变化实现惯性权重和加速因子的自适应调整,从而确定最优匹配位置。然后,基于地形特征,通过对匹配结果的可用性进行判断来进一步提高匹配定位精度。仿真实验结果表明:在陡峭地形下,本文方法的定位误差仅为传统算法的67.4%;在平坦地形下,这一结果为32.6%,匹配耗时仅为传统算法的37.1%。Securing control in complex low-altitude environments is of significant importance to modern warfare,and terrain-aided navigation is an effective means to achieve navigation and positioning in such environments.To address the issues of poor real-time performance and sensitivity to terrain undulations in traditional batch terrain matching algorithms,a terrain matching method based on adaptive particle swarm optimization is proposed in this paper.During the search and matching phase,the particle swarm optimization algorithm is utilized,superseding the traditional exhaustive search.A correlation computation model is established using sequential similarity detection,which is then employed as the fitness measure for the particles.Throughout the search iteration process,the inertia weight and acceleration factor are adaptively adjusted based on changes in particle fitness,thereby pinpointing the optimal match position.Then,based on terrain features,the usability of the matching results is assessd to further improve the match positioning accuracy.Simulation experiment results show that the positioning error of the method in this paper is only 67.4%of the traditional algorithm under steep terrain,and this result is 32.6% under flat terrain,the matching time is only 37.1% of the traditional algorithm.

关 键 词：地形辅助导航 TERCOM算法 自适应粒子群优化 匹配可用性判断 

分 类 号：V249.3[航空宇航科学与技术—飞行器设计]