In order to address the low accuracy of cable fault location and the difficulty of feature extraction in spread spectrum time domain reflectometry (SSTDR) under complex conditions such as strong impulsive noise and narrowband interference, a high-precision ranging method based on sparrow search algorithm (SSA)-optimized variational mode decomposition (VMD) combined with the Teager energy operator (TEO) was proposed. First, taking the minimum envelope entropy as the fitness function, SSA was employed to adaptively determine the optimal number of decomposition modes and penalty factor of VMD, thereby avoiding the subjectivity of empirical parameter selection. Then, the optimized VMD was used to decompose noisy cross-correlation signals, and effective intrinsic mode function (IMF) containing fault information were selected according to the maximum kurtosis criterion. Finally, TEO was applied to the selected components to enhance the instantaneous energy of fault signals and suppress residual noise. The results show that, under mixed-noise conditions and strong impulsive interference, the proposed method can effectively eliminate interference components and accurately reconstruct fault features. It is concluded that the proposed method achieves significantly higher localization accuracy and stronger noise robustness than empirical mode decomposition (EMD) and fixed-parameter VMD methods.