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Target Detection Performance Analysis of SAR Image with Different Resolutions Based on Template Matching

机译:基于模板匹配的不同分辨率SAR图像目标检测性能分析

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As the importance of analyzing system resource constrains on SAR automatically target recognition (ATR) has been noticed, more researchers start contributing to this field. In this paper, we focus on discussing the relationship between the performance of target detection and the resolution of SAR image which is regarded as one of the most important parameters of SAR imaging system. It is assumed that the resolution does not need to be good enough in target detection, but the modest reduction of resolution will provide a better trade-off between accuracy and speed. Firstly, an empirical operation is used to modify the resolution of raw images. Actually, the images with different resolutions should be derived by SAR imaging independently, but that's not the point in this paper. Then the comparison using two methods is described, the optimal detector based on Bayesian expression and the sub-optimal detector, which is known as CFAR detection. The simulated data is used to evaluate the performance of detection, and the correctness of our suspicion is demonstrated in the experiment.
机译:由于已经注意到分析系统资源限制对SAR自动目标识别(ATR)的重要性,因此越来越多的研究人员开始为这一领域做出贡献。在本文中,我们重点讨论目标检测性能与SAR图像分辨率之间的关系,该关系被认为是SAR成像系统最重要的参数之一。假定分辨率在目标检测中不需要足够好,但是分辨率的适度降低将在精度和速度之间提供更好的权衡。首先,使用经验操作来修改原始图像的分辨率。实际上,具有不同分辨率的图像应该通过SAR成像独立获得,但这不是本文的重点。然后描述了两种方法的比较,一种是基于贝叶斯表达式的最优检测器,另一种是称为CFAR检测的次优检测器。仿真数据用于评估检测性能,并在实验中证明了我们的怀疑的正确性。

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