Focus3D：一种自适应聚焦ISAR数据并为自动目标识别提供三维信息的实用方法
Focus3D: A Practical Method to Adaptively Focus ISAR Data and Provide 3-D Information for Automatic Target Recognition
AI总结：
本文提出Focus3D方法，结合聚焦算法与舰船相对雷达角度建模，通过方位角和倾斜角确定舰船姿态，为ATR提供三维信息，缩小识别范围，扩展了Melendez和Bennett的单一角度研究。
摘要：
为了提升海上舰船的自动目标识别（ATR）能力，需要一种先进的逆合成孔径雷达（ISAR）处理器——它不仅能提供聚焦图像，还能确定舰船的姿态。这能告诉我们图像显示的是侧视图（垂直平面）、俯视图（水平平面）还是介于两者之间的某个视图。如果该处理器能提供此信息，ATR处理器就能尝试将图像与舰船已知的垂直或水平特征进行匹配，并结合估算的舰船长度，缩小可能的识别范围。本文扩展了Melendez和Bennett的工作[M-B，参考文献1]，将聚焦算法与舰船相对雷达角度的建模方法相结合。在M-B中，算法仅限于单一角度，且未确定旋转平面。对于可用数据有限、难以确定姿态的短时间图像，这一假设或许可行。然而，本文使用两个角度对舰船旋转进行建模——方位角（代表水平平面内的旋转）和倾斜角（代表舰船有效 grazing 角的变化）。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
