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 0.652 7 m. Compared with the WVD method and the SPWVD method, the positioning errors are reduced by 1.288 4 and 0.683 4 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、0, and 5, and the positioning effect is the best.