北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (5): 82-86.doi: 10.13190/j.jbupt.2017-061

• 论文 • 上一篇    下一篇

基于多传感器数据融合的合成孔径声纳运动补偿算法

张羽1,2, 李更祥1,2, 张鹏飞1, 韦琳哲1, 刘纪元1   

  1. 1. 中国科学院 声学研究所, 北京 100190;
    2. 中国科学院大学, 北京 100190
  • 收稿日期:2017-04-10 出版日期:2017-10-28 发布日期:2017-11-21
  • 作者简介:张羽(1994-),男,博士生,E-mail:zhangyu515@mails.ucas.ac.cn;刘纪元(1963-),男,研究员.
  • 基金资助:
    国家高技术研究发展计划(863计划)项目(2013AA092701);中国科学院声学研究所青年英才计划项目(Y754211211)

Motion Compensation Algorithm of Synthetic Aperture Sonar Based on Multisensor Data Fusion

ZHANG Yu1,2, LI Geng-xiang1,2, ZHANG Peng-fei1, WEI Lin-zhe1, LIU Ji-yuan1   

  1. 1. Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China;
    2. University of Chinese Academy of Sciences, Beijing 100190, China
  • Received:2017-04-10 Online:2017-10-28 Published:2017-11-21

摘要: 利用集中卡尔曼滤波技术对多传感器数据进行融合得到运动误差最优估计值,实现比单一设备更高的量测精度.实验结果表明,经过数据融合后的运动补偿图像辐射性能得到提高,目标能量集中,聚焦良好.

关键词: 合成孔径声纳, 数据融合, 集中卡尔曼滤波, 运动补偿

Abstract: The data from the motion measuring system is the basis to estimate the motion errors in synthetic aperture sonar. By taking advantage of the centralized Kalman filter, the optimal estimation can be realized after multisensor data fusion, which is more accurate than any raw data. The experiment results show that motion compensation with multisensor data fused can make the image radiation performance improved, energy centralized and the target focused well.

Key words: synthetic aperture sonar, data fusion, centralized Kalman filter, motion compensation

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