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

Abstract

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.

An Efficient Analysis on the Fitting Error Caused by the Deformation of Metal Pylon in the RCS Measurement

“…In RCS measurements, complex scattering signals including the target and background are separated by the method introduced in [2][3][4], which utilizes multiple measurements during target translation along the direction of the incidence plane wave and circle fitting to process the raw measured data. The inner structure of the metal pylon is simplified as a hollow one with uniform wall thickness and is manufactured using a single homogenous material.…”

“…The target can change its azimuth and pitch angles through the rotator motion to expand the test pose. Some new rotators can also provide the target with a translation movement parallel to the direction of the plane wave, for separating the echo signal of the target from the background signal by circle fitting of the measured data [2][3][4].…”