A new time delay estimation method based on masked filtering Wigner-Ville distribution is proposed to address the issues of cross-term interference or low time-frequency concentration in common time-frequency analysis, which lead to inaccurate time delay estimation. The basic principle is to combine the amplitude spectrum ratio of the WVD time-frequency spectrum and the SPWVD time-frequency spectrum with a Gaussian function filter. By taking advantage of the SPWVD method's ability to effectively suppress cross-term interference and the high time-frequency concentration of the WVD method, the SPWVD time-frequency spectrum of the signal is used as a mask to shield the cross-terms in the WVD time-frequency spectrum, thereby obtaining a high-precision time-frequency spectrum while maintaining high time-frequency resolution. Compared with common time-frequency domain reflection methods, this method exhibits better performance in two key performance indicators, namely cross-term suppression and time-frequency concentration, and the reliability of the time delay estimation results is relatively high. This method is applied to locate weak low-resistance faults in cables in combination with the time-frequency cross-correlation function. Through comparative analysis of simulation experiments, the results show that when locating a low-resistance fault at 1.5 km in the cable, the root mean square error of the proposed method is 0.6527 m. Compared with the WVD method and the SPWVD method, the positioning errors are reduced by 1.2884 m and 0.6834 m respectively. In addition, the positioning error of this method is smaller than that of other common methods under signal-to-noise ratios of -5 dB, 0 dB, and 5 dB, and the positioning effect is the best.