표적 탐지 및 식별 성능 향상을 위한 레이더 측정치 분석

Abstract

Using artificial intelligence, radar measurements can improve the performance of target detection and identification methods. Testing data was generated from existing radar data, high-resolution range profile, and inverse synthetic aperture radar images. Radarcross section was chosen as the main parameter because it has been widely studied and its parameters are well known. To ensure thequality of the training dataset, we used simulation tools to determine which parameters had the greatest effect on the generated data. Missile models with different shapes were applied during simulations to confirm the possibility of detection and identification whensuitable parameters were applied.