To solve the problem of wide-band direction-of-arrival (DOA) estimation in the case of colored noise, this paper proposes an effective solution combining covariance matrix difference theory and eigenvector space focusing algorithm. First, based on the covariance matrix difference theory, the difference covariance matrix was decomposed, and the observation model was reconstructed by taking the corresponding eigenvector of the positive eigenvalue part to eliminate the influence of colored noise and “pseudo” peak. Then, for the obtained observation model, a new signal autocorrelation matrix was constructed, and a wide-band DOA estimation method that requires no angle prediction was derived, which is to solve the focus matrix based on the eigenvector signal subspace at different frequency points. In addition, in order to avoid the influence of the eigenvector corresponding to zero eigenvalue on the resolution threshold, the eigenvector matrix was rearranged according to the eigenvalue decreasing sequence, and the focus matrix was reconstructed from the orthogonality relationship between the nonsalient part and the flow pattern matrix of the signal array. Finally, the performances of direction finding accuracy, resolution, robustness, and complexity of the proposed algorithm were analyzed in noise background. Theoretical analysis and simulation results indicate that the method has high accuracy and robustness in the background of colored noise with low complexity and strong practicability, and there is no need to conduct angle prediction.