Tomographic imaging of a dynamic scene is addressed for the first time in this article. The effect of dynamics of the imaged object is studied for some deformation scenarios using the conventional truncated singular value decomposition (TSVD) method, which is applied in numerous static inverse scattering problems, together with variational data assimilation (DA) methods including three‐dimensional variational (3D‐VAR) and four‐dimensional variational (4D‐VAR) techniques. Results show that the DA frameworks outperform the TSVD method, which assumes the scene static, especially for objects with higher contrast. Also, it is seen that applying the conventional TSVD method makes the image blurred and distorts it for high‐speed dynamic changes, particularly when the contrast is increased. However, the proposed DA methods seem to be robust against large deformation distortions and can still detect the object.
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机译：本文首次讨论了动态场景的断层成像。使用传统的截断奇异值分解（TSVD）方法，以及包括三维变分（3D-VAR）和四维变分（4D-VAR）技术在内的变分数据同化（DA）方法，研究了成像物体在一些变形场景中的动力学影响。结果表明，DA框架优于假设场景静态的TSVD方法，特别是对于对比度较高的物体。此外，可以看出，应用传统的TSVD方法会使图像模糊并使其失真，以适应高速动态变化，特别是在对比度增加时。然而，所提出的 DA 方法似乎对大变形变形具有鲁棒性，并且仍然可以检测物体。
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