Adverse weather conditions create significant challenges to autonomous systems, relying on system based perception. While individual modalities like cameras and radar offer complementary strengths, their fusion – especially at an early stage – remains a key research area. This talk explores a modality-balanced early fusion approach that integrates sensor data to enhance perception robustness in adverse weather.