A study on application of flow velocity distribution measurement of drift ice of Okhotsk coast ice sea navigation using Radar images

鄂霍茨克沿岸冰海航海雷达图像流冰流速分布测量应用研究

• 批准号: 16510131
• 负责人: TAKAGI Toshiyuki
• 金额: $ 2.05万
• 依托单位: Kushiro National College of Technology
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2004
• 资助国家: 日本
• 起止时间: 2004 至 2005
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-16510131/
• 关键词: Okhotsk sea; Radar image; Block matching method; Sub pixel; Neural networks; サブピクセル精度; PIV; 濃度相関法; 強化学習; 海氷航行

(1)Speed-up of movement analysis of drift ice radar imageTo get a time change in the drift ice distribution automatically the block match method can be applied to the drift ice radar image. However, the movement of the drift ice distribution is complex, and a lot of errors occur in a usual block match analysis. Moreover, it is necessary not only to understand a present situation to secure a safe sea route but also forecast the situation in the future. And, it is necessary to achieve this processing ideally automatically and in real time. An analytical result of the block match method can be used as input information on the forecast processing. However, because the amount of the calculation is very large in a usual block match method, real time processing is difficult. Then, to measure speeding up and making of the drift ice analysis highly accurate in this research, the improvement technique of the block match is developed.(2)Sub-pixel estimation method using neural networksA sub pixel estimation technique using neural networks has been presented for obtaining flow velocity distribution of sea ice. If we need precise displacement of the flow of the drift ice, sub-pixel estimation of best matching location is required. The sub-pixel accuracy is obtained by applying an interpolation scheme to the correlation peak within the interrogation area. Traditionally, the Gauss function has been used as peak-fitting function. However the sub-pixel accuracy is dependent upon both a bias error and a random error. It is very difficult to identify peak fitting function for all applied images. Then, we propose the method that uses neural networks which has a priori knowledge about applied image. We show the proposed technique achieved good results from the radar image.

(1)流冰雷达图像运动分析的加速为了自动获得流冰分布的时间变化，可以将块匹配方法应用于流冰雷达图像。但流冰分布运动复杂，通常的块匹配分析会出现很多误差。此外，不仅需要了解当前状况以确保安全的海上航线，还需要预测未来的状况。并且，有必要理想地自动且实时地实现该处理。块匹配方法的分析结果可以用作预测处理的输入信息。然而，由于通常的块匹配方法的计算量很大，所以实时处理比较困难。然后,为了提高本研究中流冰分析的速度和精度,开发了块匹配的改进技术。(2)基于神经网络的亚像素估计方法提出了基于神经网络的亚像素估计技术。用于获取海冰的流速分布。如果我们需要流冰流的精确位移，则需要对最佳匹配位置进行亚像素估计。亚像素精度是通过对询问区域内的相关峰值应用插值方案来获得的。传统上，高斯函数被用作峰值拟合函数。然而，子像素精度取决于偏置误差和随机误差。识别所有应用图像的峰值拟合函数是非常困难的。然后，我们提出了使用具有有关应用图像的先验知识的神经网络的方法。我们表明所提出的技术从雷达图像中取得了良好的结果。

项目成果

Near-wall Brownian diffusion of nanoparticles examined by three-dimensional ratiometric total internal reflection fluorescence microscopy (3-D R-TIRFM)

通过三维比例全内反射荧光显微镜 (3-D R-TIRFM) 检查纳米粒子的近壁布朗扩散

• 发表时间: 2004
• 期刊: Experiments in Fluids 37
• 作者: Kunio HARA;Mihoko MORI;Tatsuya ISHITAKE;Hiroki KITAJIMA;Kazuhiro SAKAI;Kenji NAKAAKI;Hiroshi JONAI;原邦夫;原邦夫;高木敏幸;柳川和徳;T.Takagi;Kazunori Yanagawa;高木敏幸 他;柳川和徳 他;高木 敏幸;K.D.Kihm
• 通讯作者: K.D.Kihm

Visualization of the Drift Ice Motion on the Okhotsk Sea using Modified Cross Correlation

使用修正互相关法对鄂霍次克海流冰运动进行可视化

• 发表时间: 2004
• 期刊: Proc.Of The 19^<th> International Symposium of Okhotsk Sea &Sea Ice
• 作者: Kunio HARA;Mihoko MORI;Tatsuya ISHITAKE;Hiroki KITAJIMA;Kazuhiro SAKAI;Kenji NAKAAKI;Hiroshi JONAI;原邦夫;原邦夫;高木敏幸;柳川和徳;T.Takagi;Kazunori Yanagawa;高木敏幸 他;柳川和徳 他;高木 敏幸
• 通讯作者: 高木 敏幸

An Acceleration Scheme for Motion Analysis of Sea-Ice Radar Images

海冰雷达图像运动分析的加速方案

• 发表时间: 2006
• 期刊: Proc. of The 2006 IEICE General Conference
• 作者: Kunio HARA;Mihoko MORI;Tatsuya ISHITAKE;Hiroki KITAJIMA;Kazuhiro SAKAI;Kenji NAKAAKI;Hiroshi JONAI;原邦夫;原邦夫;高木敏幸;柳川和徳;T.Takagi;Kazunori Yanagawa
• 通讯作者: Kazunori Yanagawa

A Sub-pixel Estimation of Drift Ice Motion on Radar Images using Neural Networks

使用神经网络对雷达图像流冰运动进行亚像素估计

• 发表时间: 2006
• 期刊: The 21st International Symposium on Okhotsk Sea & Sea Ice
• 作者: Kunio HARA;Mihoko MORI;Tatsuya ISHITAKE;Hiroki KITAJIMA;Kazuhiro SAKAI;Kenji NAKAAKI;Hiroshi JONAI;原邦夫;原邦夫;高木敏幸
• 通讯作者: 高木敏幸

流氷レーダ画像の運動解析の高速化

加速流冰雷达图像的运动分析

• 发表时间: 2006
• 期刊: 電子情報通信学会2006年総合大会講演論文集
• 作者: Kunio HARA;Mihoko MORI;Tatsuya ISHITAKE;Hiroki KITAJIMA;Kazuhiro SAKAI;Kenji NAKAAKI;Hiroshi JONAI;原邦夫;原邦夫;高木敏幸;柳川和徳
• 通讯作者: 柳川和徳