A Novel Data Segmentation-Based Approach for Validating the Narrowband Radar Data by the Feature Selective Validation Method

Abstract

More and more electromagnetics analyses need more detailed-level data validation technologies, which can focus on the specific data region. The feature selective validation (FSV) method is a key electromagnetics validation tool, which was adopted in 2008 as the core of 1597.1 standard for validation of computational electromagnetics computer modeling and simulations. However, despite its successful performance for electromagnetic compatibility (EMC) data, it still comes to apply to the validation of narrowband radar data, which, differing from EMC data, is quite problematic. For this reason, this paper proposes a novel approach, which is called segment FSV (S-FSV), to deal with the narrowband radar data. This approach divides the data into several segments, extracts the peak and oscillation regions, allocates an individual importance degree to each segment, and generates validation results for all segments. Finally, the efficiency and feasibility of the proposed approach is corroborated by the statistical results in a narrowband radar data survey. The proposed S-FSV approach is shown to outperform the traditional FSV one in reflecting the expert opinions and to be more suitable for validation of such data.