A fast and robust method for target and background estimation in RCS measurements based on ‘hyperaccurate’ algebraic circle fit

Abstract

I Abstract-The sample data points, which are obtained in radar minimize various approximate distances [7], [16], [17], which cross section (RCS) measurement, will distribute theoretically on are called algebraic fits. The circle fitting algorithm used in [5] a circle when the target moving along the direction of the is one kind of geometric fits, which is time-consuming and not illuminating plane wave. The radius of the circle represents the the best algorithm to deal with the RCS measurement data set.target signal and the center of the circle represents the background signal. Based on theoretical analysis and numericalIn this paper, a so-called 'hyperaccurate' algebraic circle simulation, we have implemented the fast 'hyperaccurate' fitting algorithm is implemented, which is well designed and algebra circle fitting algorithms to fit circles to measurement first proposed by N.Chemov in 2009 [7]. This algorithm is data points. At the same time, a robust least-median-of-squares fast and appears to be nearly as accurate as geometric fits. method has been implemented to eliminate the outliers. According to the fitting accuracy requirement of the target and background, the sampling number and the sampling range are determined. Two different spheres are measured with this algorithm in Compact Antenna Test Range (CATR) and their target signals and background signals are well separated, which improves the measurement accuracy.