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Analytical SAR-GMTI Principles

机译:SAR-GMTI分析原理

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This paper provides analytical principles to relate the signature of a moving target to parameters in a SAR system. Our objective is to establish analytical tools that could predict the shift and smearing of a moving target in a subaperture SAR image. Hence, a user could identify the system parameters such as the coherent processing interval for a subaperture that is suitable to localize the signature of a moving target for detection, tracking and geolocating the moving target. The paper begins by outlining two well-known SAR data collection methods to detect moving targets. One uses a scanning beam in the azimuth domain with a relatively high PRF to separate the moving targets and the stationary background (clutter); this is also known as Doppler Beam Sharpening. The other scheme uses two receivers along the track to null the clutter and, thus, provide GMTI. We also present results on implementing our SAR-GMTI analytical principles for the anticipated shift and smearing of a moving target in a simulated code. The code would provide a tool for the user to change the SAR system and moving target parameters, and predict the properties of a moving target signature in a subaperture SAR image for a scene that is composed of both stationary and moving targets. Hence, the SAR simulation and imaging code could be used to demonstrate the validity and accuracy of the above analytical principles to predict the properties of a moving target signature in a subaperture SAR image.
机译:本文提供了将运动目标的签名与SAR系统中的参数相关联的分析原理。我们的目标是建立分析工具,以预测子孔径SAR图像中移动目标的移动和拖尾现象。因此,用户可以识别系统参数,例如子孔径的相干处理间隔,该子孔径适合于定位移动目标的特征以检测,跟踪和地理定位移动目标。本文首先概述了两种著名的SAR数据收集方法来检测运动目标。一种是使用具有较高PRF的方位角域中的扫描光束将运动目标与静止背景(杂波)分开;这也称为多普勒光束锐化。另一种方案是沿轨道使用两个接收器来使杂波归零,从而提供GMTI。我们还介绍了执行SAR-GMTI分析原理的结果,以预期的运动目标在模拟代码中的移动和拖尾。该代码将为用户提供一个工具,以更改SAR系统和移动目标参数,并针对由固定目标和移动目标组成的场景,预测子孔径SAR图像中移动目标签名的属性。因此,SAR模拟和成像代码可用于证明上述分析原理的有效性和准确性,以预测子孔径SAR图像中移动目标签名的特性。

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