RCS Sequence Prediction for Multiple Scatterers Based on Characteristic Modes

This paper proposes a method, utilizing the characteristic modes (CMs) of the scatterers, to achieve rapid and accurate prediction of radar cross section (RCS) sequence for multiple scatterers. The linear reconstruction of the scatterers' RCS sequence by using CMs requires information about the scatterers' flight position and attitude angles. Therefore, predicting the RCS sequence over a specific period of time can be transformed into forecasting the scatterers' position and attitude parameters during the period. By leveraging neural networks, the position and attitude angle variations of the multiple scatterers can be predicted rapidly and accurately, enabling rapid and accurate prediction of the RCS sequence throughout the scatterers' flight. Numerical example confirms the accuracy and efficiency of the proposed method.