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Using Kasa Method to Separate Target's RCS Characters from Background in Electromagnetic Sensing within Anechoic Chamber Measurement

机译:使用KASA方法将目标的RCS字符与电子传感器中的背景中的背景分开,在AneChice腔室测量内

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In many cases non-cooperative things that have no available ID numbers need to be identified via electromagnetic sensing. In order to obtain target's accuracy Radar Cross Section (RCS) character, separating target signal from background is a necessary step in RCS measurement of heavy targets mounted on a metal pylon and both geometric fit and algebraic fit can be applied in the separation procedure. In this paper, the feasibility of Kasa method in separation of target signal and background signal is researched. The bias of Kasa method under whole circle circumstance is deducted, and the validation of simulation data using Kasa method has been accomplished. The separation result of two measurement data is compared between Kasa method and ODR (Orthogonal Distance Regression) method, and the comparison result shows that Kasa method can be used in separation of background and target signal.
机译:在许多情况下,不需要通过电磁感测来识别不可用ID号的非合作措施。为了获得目标的精度雷达横截面(RCS)特征,从背景中分离目标信号是安装在金属塔上的重物的RCS测量中的必要步骤,并且可以在分离过程中施加几何配合和代数拟合。本文研究了KASA方法在分离目标信号和背景信号中的可行性。扣除了全圆环境下的KASA方法的偏差,并完成了使用KASA方法的模拟数据的验证。在KASA方法和ODR(正交距离回归)方法之间比较了两个测量数据的分离结果,并且比较结果表明KASA方法可用于背景和目标信号的分离。

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