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Aiming at the issue of less available navigation information underwater, this paper presents the utilization of polarized light to aid in correcting yaw in an integrated navigation system combining Doppler Velocity Logger (DVL) and Strapdown Inertial Navigation System (SINS) for underwater applications. Initially, the characteristics of sunlight propagation through atmospheric scattering, refraction at the gas-water interface, and underwater scattering are examined. And the yaw algorithm of underwater polarized light is determined using the polarization distribution mode by utilizing the orthogonal property of E-vector and sun direction vector. Then, a SINS/DVL/underwater polarized light integrated navigation system is designed through a Federated Kalman Filter based above yaw results. The performance and accuracy of the system have been verified through simulation. Results confirm that the proposed scheme not only keeps the yaw error within 0.05°, but also enhances the overall accuracy of the navigation system compared with the traditional scheme which only uses the speed error for data fusion.

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Integrated Navigation Yaw Correction Based on Underwater Polarized Light Assistance

  • 会议论文

  • 发表日期：

    2025年

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  • Jicheng Ding,
  • Jiaxuan Hou,
  • Na Liu,
  • Zhijian Pan,
  • Jianhua Cheng

摘要

Aiming at the issue of less available navigation information underwater, this paper presents the utilization of polarized light to aid in correcting yaw in an integrated navigation system combining Doppler Velocity Logger (DVL) and Strapdown Inertial Navigation System (SINS) for underwater applications. Initially, the characteristics of sunlight propagation through atmospheric scattering, refraction at the gas-water interface, and underwater scattering are examined. And the yaw algorithm of underwater polarized light is determined using the polarization distribution mode by utilizing the orthogonal property of E-vector and sun direction vector. Then, a SINS/DVL/underwater polarized light integrated navigation system is designed through a Federated Kalman Filter based above yaw results. The performance and accuracy of the system have been verified through simulation. Results confirm that the proposed scheme not only keeps the yaw error within 0.05°, but also enhances the overall accuracy of the navigation system compared with the traditional scheme which only uses the speed error for data fusion.