农业机械学报2017，Vol.48Issue(7)：38-45,8.DOI:10.6041/j.issn.1000-1298.2017.07.005
基于IPSO-UKF的水草清理作业船组合导航定位方法
Integrated Navigation Positioning Method Based on IPSO-UKF for Aquatic Plants Cleaning Workboat
摘要
Abstract
In the aquatic plants cleaning process of crab culture,in order to reduce labor intensity of the farmers and improve the positioning accuracy of navigation,a kind of DGPS and vision integrated navigation positioning method was designed with immune particle swarm optimization (IPSO) to optimize the trace of Kalman filter,which combined the advantages of DGPS and visual navigation,and was applied to aquatic plants cleaning workboat.Firstly,the integrated navigation model was established,and then the state equation and observation equation of the system were obtained.In order to solve the divergence problem of UKF filtering for navigation model,PSO was used to obtain new particles,and immune algorithm was introduced to avoid premature phenomenon of PSO.Combining with UKF,the navigation model was filtered,and the new position coordinates were obtained.At last,the comparative experiment was conducted by simulation and navigation experiment.Simulation experiment results showed that the root mean square error (RMSE) at east and north positions of the proposed method were reduced by 46.09％ and 71.51％ compared with DGPS navigation,and reduced by 23.92％ and 58.26％ compared with integrated navigation,respectively.Navigation experiment results showed that in the same longitude position the latitude error of proposed method was reduced by 22.69％ and 9.14％ compared with DGPS and integrated navigation,respectively.The results showed that the navigation time of the proposed method was reduced by 4.77％ and 4.32％ compared with DGPS and integrated navigation,respectively.关键词
河蟹养殖/水草清理作业船/视觉导航/DGPS/IPSO-UKFKey words
crab culture/aquatic plants cleaning workboat/visual navigation/DGPS/IPSO-UKF分类
信息技术与安全科学引用本文复制引用
阮承治,赵德安,刘晓洋,陈旭,姬伟,贾伟宽..基于IPSO-UKF的水草清理作业船组合导航定位方法[J].农业机械学报,2017,48(7):38-45,8.基金项目
国家自然科学基金项目(31571571,61573170),高等学校博士学科点专项科研基金项目(20133227110024),江苏省高校优势学科建设项目(PAPD),镇江市重点研发(现代农业)计划项目(NY2015022),江苏省普通高校研究生科研创新计划项目(KYLX15_1075),福建省教育厅中青年项目(JAT160506)和武夷学院校科研基金项目(XD201504) （31571571,61573170）
