提出自适应聚焦ISAR数据并获取三维姿态信息的方法，提升舰船自动识别准确率。
Focus3D: A Practical Method to Adaptively Focus ISAR Data and Provide 3-D Information for Automatic Target Recognition
- 结合聚焦算法与双角度建模（方位角与俯仰角），实现动态姿态估计。
- 可区分舰船的侧视、顶视及中间视角，支持多姿态匹配识别。
- 适用于海上舰船识别场景，尤其适合数据有限的短时成像条件。
提升海上舰船自动目标识别（ATR）精度需依赖先进的ISAR处理器——不仅能生成清晰聚焦图像，还能确定舰船姿态。这能判断图像是侧视（垂直平面）、顶视（水平平面）还是中间视角。若处理器提供此信息，ATR系统可将图像与已知的垂直或水平特征匹配，并结合估算的舰船长度缩小识别范围。本文在Melendez and Bennett [M-B, 参考文献1]工作的基础上，将聚焦算法与舰船相对雷达角度的建模方法相结合。M-B方法仅限于单一角度且未确定旋转平面，该假设在数据有限的短时成像中尚可接受。而本文通过两个角度建模：方位角（水平面旋转）和俯仰角（有效入射角变化），实现更精确的姿态估计。
原文摘要 · Abstract (English)
To improve ATR identification of ships at sea requires an advanced ISAR processor - one that not only provides focused images but can also determine the pose of the ship. This tells us whether the image shows a profile (vertical plane) view, a plan (horizontal plane) view or some view in between. If the processor can provide this information, then the ATR processor can try to match the images with known vertical or horizontal features of ships and, in conjunction with estimated ship length, narrow the set of possible identifications. This paper extends the work of Melendez and Bennett [M-B, Ref. 1] by combining a focus algorithm with a method that models the angles of the ship relative to the radar. In M-B the algorithm was limited to a single angle and the plane of rotation was not determined. This assumption may be fine for a short time image where there is limited data available to determine the pose. However, the present paper models the ship rotation with two angles - aspect angle, representing rotation in the horizontal plane, and tilt angle, representing variations in the effective grazing angle to the ship.
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