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MTI data clustering and formation recognition

机译：MTI数据聚类和编队识别

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Image exploitation technology approaches have generally focused on the detection and spatial analysis of stationary groups of objects on the ground using various sensors. While spatial arrangement is clearly necessary in analyzing military formations, it is usually not sufficient. Typically the arrangement must be examined within some context in order to interpret a pattern of deployment. For moving objects the spatial arrangement of the group relative to the direction of motion is key to recognizing the formation. By examining ground moving target indicator (MTI) radar data over time, motion can be inferred and used to establish a context for interpreting the spatial arrangement of the data. New techniques that exploit the multitemporal nature of MTI data are described. The first is a space-time clustering technique that locates compact groups of objects that persist in time. The technique Is an application of Marr and Hildreth's edge detection methodology to the dual problem of region segmentation, or more accurately, volumetric segmentation of space-time. The second technique is based on the use of the Hough transform for recognizing moving formations such as columns, wedges, and lines abreast by analyzing the shape of clustered MTI detections (specifically the orientation of linear arrangements within the group) with respect to their direction of motion. Preliminary results from simulated MTI data sets are presented
机译：图像开发技术方法通常集中于使用各种传感器对地面上静止的物体组进行检测和空间分析。尽管空间布局显然是分析军事编队所必需的，但通常是不够的。通常，必须在某种情况下检查该安排，以解释部署模式。对于移动物体，组相对于运动方向的空间布置是识别地层的关键。通过检查随时间变化的地面移动目标指示器（MTI）雷达数据，可以推断出运动并将其用于建立解释数据空间布置的上下文。描述了利用MTI数据的多时间性质的新技术。第一种是时空聚类技术，用于定位在时间上持久存在的紧凑对象组。该技术将Marr和Hildreth的边缘检测方法应用于区域分割的双重问题，或更准确地说是时空的体积分割。第二种技术是基于霍夫变换的使用，通过分析聚类MTI检测的形状（特别是组内线性排列的方向）相对于它们的方向，来识别并列移动的岩层（例如，圆柱，楔形和直线）。运动。给出了来自模拟MTI数据集的初步结果

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