RCS Prediction Acceleration and Reduction of Table Size for the Angular Division Algorithm

Abstract

The method of shooting and bouncing rays has been successfully used to predict the radar cross section (RCS) of electrically large and complex target models. However, this method has a demerit that its prediction time is very long when targets are electrically large and complex. Therefore, we propose the hybrid angular division algorithm (HADA) that accelerates prediction of RCS for electrically large and complex target models. This method improves the angular division algorithm (ADA), by incorporating a more efficient way of dealing with patches on planes that meet at angles between (90 – α)° and (90 + α)°, where α is the so-called 'critical angle'. A critical angle delimits a range of angles in which the effects of double reflections between patches are dominant. We perform ADA for a patch-pair which satisfies the condition of critical angles. We used the proposed algorithm to calculate the RCS of a model battleship; compared to ADA, HADA reduces prediction time by ≥ 30% without loss of accuracy.