A new method called kernel adaptive MFA (KAMFA) was developed to improve radar target recognition. KAMFA extracts nonlinear features from radar data by using a special technique. It assigns weights to each sample based on their similarities, making the method more effective in distinguishing between different targets. The researchers tested KAMFA on three datasets and found that it produced promising results in recognizing ground targets.