Aiming at the issue of co-frequency interference between shipborne radars in complex battlefield environments, an independent component analysis technique based on an improved crow search algorithm is proposed to separate co-frequency signals. First of all, the optimization performance and convergence speed of the algorithm are enhanced by utilizing the reverse learning method, dynamic perception probability, golden sine operator, and Levy flight. Then, the algorithm is integrated with the independent component analysis technique. Taking kurtosis as the objective function, the optimal separation matrix is determined by implementing the improved crow search algorithm. Finally, the matrix is applied to separate the received mixed signals. The simulation findings demonstrate that the proposed independent component analysis technique based on the improved crow search algorithm effectively separates the radar co-frequency signals and accomplishes the goal of anti-co-frequency interference.