The accurate measurement of high-resolution solar spectral irradiance (SSI) and its variations at the top of the atmosphere is crucial for solar physics, the Earth’s climate, and the in-orbit calibration of optical satellites. However, existing space-based solar spectral irradiance instruments achieve high-precision SSI measurements at the cost of spectral resolution, which falls short of meeting the requirements for identifying fine solar spectral features. Therefore, this paper proposes a new method for reconstructing high-resolution solar spectral irradiance based on a residual channel attention network. This method considers the stability of SSI spectral features and employs residual channel attention blocks to enhance the expression ability of key features, achieving the high-accuracy reconstruction of spectral features. Additionally, to address the issue of excessively large output features from the residual channel attention blocks, a scaling coefficient adjustment network block is introduced to achieve the high-accuracy reconstruction of spectral absolute values. Finally, the proposed method is validated using the measured SSI dataset from SCIAMACHY on Envisat-1 and the simulated dataset from TSIS-1 SIM. The validation results show that, compared to existing scaling coefficient adjustment algorithms, the proposed method achieves single-spectrum super-resolution reconstruction without relying on external data, with a Mean Absolute Percentage Error (MAPE) of 0.0302% for the reconstructed spectra based on the dataset. The proposed method achieves higher-resolution reconstruction results while ensuring the accuracy of SSI.