哈尔滨工程大学学报Issue(9)：1124-1130,7.DOI:10.3969/j.issn.1006-7043.201209033
水中非合作运动磁性目标跟踪及参数估计
Study on the tracking and parameter estimating of unknown moving magnetism objects
摘要
Abstract
In aiming to examine the tracking and parameter estimating of unknown moving magnetic objects, a mag-netic target tracking method based on Hopfield neural network and magnetic gradient tensor orientation combining particle filter was presented. The Hopfield neural network and magnetic gradient tensor orientation may provide some more optimized particles for particle filter algorithm. Thus the diversity of particles is improved in a particle filter algorithm. The algorithm was found able to effectively conquer the degeneration of particles, and simultaneous-ly ensure the speed and precision of dynamic tracking, and solve the problem on declining of signal-to-noise in far field magnetic localization. The results of simulation and magnetic ship model magnetic orientation experiment show the validity of this algorithm. This algorithm will have some significance in martial and civil field such as submarine magnetic detection, magnetic defense of military port, and unexploded ordnance ( UXO) detection and orientation.关键词
磁性目标跟踪/Hopfield网络/磁梯度张量定位/粒子滤波Key words
magnetic target tracking/Hopfield network/localization by magnetic gradient tensor orientation/parti-cle filter分类
信息技术与安全科学引用本文复制引用
高俊吉,刘大明,周国华..水中非合作运动磁性目标跟踪及参数估计[J].哈尔滨工程大学学报,2013,(9):1124-1130,7.基金项目
国家自然科学基金资助项目（51107145）． （）
