现代雷达2023，Vol.45Issue(12)：62-68,7.DOI:10.16592/j.cnki.1004-7859.2023.12.009
基于改进型支持向量机的目标微弱磁异常信号检测方法研究
A Study on Weak Magnetic Anomaly Detection Algorithm of Target Based on Improved Support Vector Machine
摘要
Abstract
Magnetic anomaly detection(MAD)has the characteristic of stable propagation across different medium.It has advanta-ges that are not influenced by hydrometeorological conditions and environmental medium(such as water,air,sand,soil).As a re-sult,it has been a research hotspot in industrial and military fields.With the combination of Unmanned Aerial Vehicle platform,the working efficiency of MAD is greatly improved,especially in extreme environments.However,the magnetic anomaly signal for small buried targets(such as unexploded bombs,underground cables and pipelines,underground metal wastes)is usually weaker compared with environmental noise,and the effective signal is usually disturbed by environmental noise.Data quality is further af-fected by dynamic noise introduced by drone platforms.Traditional target detection algorithms are effective in conditions with good data quality and high signal-to-noise ratio.These algorithms failed to detect the existences of buried targets under complex condi-tions.An improved genetic support vector machine(GSVM)algorithm is proposed to resolve this problem.To improve the effi-ciency of the proposed algorithm,the hyperparameters are optimized by using a genetic algorithm.The computational efficiency and accuracy of the algorithm are compared with traditional algorithms in the numerical experiments and field data applications.The re-sults prove that the accuracy of detection and identification of buried small targets has been effectively improved by the proposed GSVM algorithm.关键词
磁异常检测/掩埋小目标/遗传算法/改进型支持向量机Key words
magnetic anomaly detection/bury small targets/genetic algorithm/improved support vector machine分类
电子信息工程引用本文复制引用
杨宇欣,张鹏飞,李宝聚,沈莹,陈之岳,杨晓宝..基于改进型支持向量机的目标微弱磁异常信号检测方法研究[J].现代雷达,2023,45(12):62-68,7.基金项目
国家重点研发计划资助项目(2022YFC3104000) （2022YFC3104000）
