计算机与数字工程2024，Vol.52Issue(3)：841-845,891,6.DOI:10.3969/j.issn.1672-9722.2024.03.035
基于AGPF的目标定位精度改善方法
Target Positioning Accuracy Improvement Method Based on Adaptive Genetic Algorithms Particle Filter
摘要
Abstract
In order to solve the problem that traditional genetic algorithm particle filter is easy to fall into local optimization due to constant genetic operation parameters,an adaptive method is introduced into genetic algorithm particle filter,and an adap-tive genetic algorithm particle filter is proposed.The principle of dominant inheritance changes the probability of crossover and muta-tion with the change of particle fitness,so as to retain the dominant particles as much as possible while generating new dominant par-ticles more effectively,jumping out of local optimum.The adaptive genetic algorithm particle filter is applied to the established dy-namic state space model,compared with the performance of the genetic algorithm particle filter by simulation.The results show that the introduction of adaptive method can increase the effective particle number of the algorithm,effectively solve the problem of pre-mature algorithm and improve the filtering accuracy,which is very effective for improving the accuracy of dynamic target position-ing.关键词
动态状态空间模型/自适应/目标定位/遗传算法/粒子滤波Key words
dynamic state space model/adaptive/target positioning/genetic algorithm/particle filter分类
生物科学引用本文复制引用
蔡明,李国华,季茜,李培德..基于AGPF的目标定位精度改善方法[J].计算机与数字工程,2024,52(3):841-845,891,6.基金项目
湖北省气象局重点科研项目(编号:2022Z04)资助. （编号:2022Z04）
