雷达截面测量数据处理方法的改进

在进行雷达截面（RCS）测量原始数据的处理时，传统方法是对这些数据直接进行简化和统计处理，得到能概括目标散射特征的数据。本文应用格拉布斯检验方法和卡尔曼滤波方法，分别对静态和动态测试数据的异常值进行预先判别、剔除处理，然后再对原始数据进行平滑处理和统计分析，从而提高了处理结果的置信度，更准确地表征目标的RCS特性。

Improvement of RCS Data Processing Method

The conventional method to process raw RCS data is direct data reduction and statistical processing to get data that outlines the scattering signatures of the target. Using Grubbs test method and Kalman fiher method, this paper performs smoothing and statistical analysis of the raw data following pre-identification and elimination of outliers in static and dynamic test data. This increases the level of confidence in the processing results and represents the RCS signatures of the target in a more accurate manner.