基于Sage-Husa算法的拖曳式Overhauser海洋磁场传感器海浪磁场噪声实时抑制方法
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  • 英文篇名:Real-time Reduction of Magnetic Noise Associated with Ocean Waves via Sage-Husa Algorithm for Towed Overhauser Marine Geomagnetic Sensor
  • 作者:葛健 ; 董浩斌 ; 刘欢 ; 罗望 ; 柏明明 ; 邱香域 ; 袁志文 ; 刘咏华 ; 朱俊 ; 张海洋
  • 英文作者:Ge Jian;Dong Haobin;Liu Huan;Luo Wang;Bai Mingming;Qiu Xiangyu;Yuan Zhiwen;Liu Yonghua;Zhu Jun;Zhang Haiyang;School of Automation,China University of Geosciences;Science and Technology on Near-Surface Detection Laboratory;Institute of Geophysics and Geomatics,China University of Geosciences;
  • 关键词:Sage-Husa算法 ; Kalman滤波器 ; 拖曳式磁测 ; Overhauser海洋磁场传感器 ; 磁场噪声实时抑制 ; 地球物理
  • 英文关键词:Sage-Husa algorithm;;Kalman filter;;towed magnetic survey;;overhauser marine magnetic sensor;;real-time reduction of magnetic noise;;geophysics
  • 中文刊名:DQKX
  • 英文刊名:Earth Science
  • 机构:中国地质大学自动化学院;近地面探测技术重点实验室;中国地质大学地球物理与空间信息学院;
  • 出版日期:2018-10-15
  • 出版单位:地球科学
  • 年:2018
  • 期:v.43
  • 基金:青岛海洋科学与技术国家实验室开放基金项目(No.QNLM2016ORP0201);; 国家自然科学基金项目(Nos.41474158,41504137);; 国家重大科学仪器设备开发专项(No.2014YQ100817);; 中国博士后科学基金项目(No.2016M592410);; 科技部中小企业发展专项资金项目(No.14C26214202344);; 近地面探测技术重点实验室开放基金项目(Nos.TCGZ2015A008,TCGZ2016A005)
  • 语种:中文;
  • 页:DQKX201810038
  • 页数:7
  • CN:10
  • ISSN:42-1874/P
  • 分类号:462-468
摘要
利用Weaver海浪模型,对拖曳式Overhauser海洋磁场传感器海浪磁噪声与深度、波幅等之间的关系进行了理论分析,证明了在极端海况条件下对海浪磁噪声进行抑制的必要性.为提高海洋磁测灵敏度,提出了一种基于改进的Sage-Husa自适应Kalman算法的海浪磁场噪声抑制方法.仿真结果表明,该方法能在不需要先验的噪声统计或实时参考噪声的情况下,实现磁场噪声协方差的快速收敛;且与常规的Sage-Husa算法相比,改进后的Sage-Husa算法降低了对初始参数的依赖性.另外,设计了一种拖曳式Overhauser海洋磁场传感器测试仪来测试上述算法.对比结果表明该方法不仅实现了磁场噪声统计参数的自适应估计,而且比经典Kalman滤波具有更好的滤波效果;此外,海浪磁噪声的功率谱密度由50 p T/Hz1/2@1Hz下降到6 p T/Hz1/2@1Hz.
        Based on Weaver's model,we analyze the magnetic noise variations of the towed Overhauser marine magnetic sensor associated with the different ocean depths,wave periods and amplitudes in theory,proving the necessity of suppressing the magnetic noise in the extreme ocean conditions. In this paper,we propose a novel real-time reduction method of the magnetic noise via an improved SageHusa adaptive Kalman filter( KF) to improve the sensor sensitivity. The simulation results show that the proposed method could achieve the fast convergence of the covariance of magnetic noise without the priori noise statistics or real-time reference noise. Furthermore,thedependency on the initial parameters is reduced compared with the standard Sage-Husa algorithm. In addition,we implement a towed Overhauser marine magnetometer to test the proposed method. Over all,the comparison experiments show that the proposed method not only realizes the adaptive estimation of the magnetic noise statistics,but also has better suppression effect than the standard KF. The power spectral density of the magnetic noise is reduced to 6 p T/Hz1/2@ 1 Hz from 50 p T/Hz1/2@ 1 Hz after flitting.
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