基于物像共轭模型的IRST系统动态像移计算方法与验证
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中国科学院上海技术物理研究所

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TN215

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中国科学院上海技术物理研究所三期创新项目(Q-ZY-108)


Dynamic Image Motion Calculation Method and Verification for IRST system Based on Object-image Conjugate Model
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Shanghai Institute of Technical Physics Chinese Academy of Sciences

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Phase III Innovation Research Project of Shanghai Institute of Technical Physics Chinese Academy of Sciences (Q-ZY-108)

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    摘要:

    红外搜索与跟踪(IRST)系统作为现代战场中重要的被动探测装备,其成像质量直接决定目标探测与跟踪精度。在动态环境下,由于目标和载体间存在相对运动,导致目标在像平面上产生像移,不仅引起图像质量退化,还对目标的跟踪与捕获带来困难。有效抑制像移需以高精度测量为前提,进而实现补偿控制。针对该问题,提出一种基于坐标变换的动态像移计算方法。首先,建立动态环境下IRST系统的物像共轭模型,通过坐标变换明晰物像矢量的映射关系,实现像移量的精确量化。其次,搭建六自由度运动平台实验系统,模拟载体不同姿态扰动下的运动工况,对目标像移进行实际测量。实验结果表明,理论计算像移值与实测数据高度吻合,偏差小于2个像素(RMS),相对误差优于0.67%。该方法为动态像移的高精度补偿提供了有效技术途径,对提升IRST系统在复杂环境中的成像稳定性具有重要应用价值。

    Abstract:

    As an essential passive detection equipment in modern battlefields, the Infrared Search and Track (IRST) system’s imaging quality directly determines the accuracy of target detection and tracking. In dynamic environments, the relative motion between the target and the carrier causes image motion on the image plane, which not only degrades image quality but also poses difficulties for target tracking and acquisition. Effective suppression of image motion requires high-precision measurement as a prerequisite to achieve compensation control. To address this issue, a method for calculating dynamic image motion based on coordinate transformation is proposed. Firstly, an object-image conjugate model for the IRST system in dynamic environments is established, and the mapping relationship between object and image vectors is clarified through coordinate transformation to achieve accurate calculation of image motion displacement. Secondly, a six-degree-of-freedom motion platform experimental system is constructed to simulate various motion conditions under different carrier attitude disturbances and measure target image motion. Experimental results demonstrate that the theoretically calculated image motion values are highly consistent with the measured data, with a deviation of less than 2 pixels (RMS) and a relative error better than 0.67%. This method provides an effective technical approach for high-precision compensation of dynamic image motion and has important application value for improving the imaging stability of IRST systems in complex environments.

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  • 收稿日期:2025-09-04
  • 最后修改日期:2025-11-11
  • 录用日期:2025-12-23
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