A Method for FM Signal Localization Based on Wavelet Transform and Swin Transformer

Frequency Modulation (FM) signals exhibit robust stability due to their reduced susceptibility to environmental factors and noise interference. However, as the complexity of signal propagation environments continues to increase, existing FM-based localization methods demonstrate suboptimal performance in such intricate settings. Consequently, there is a pressing need to explore novel localization techniques. This paper proposes an end-to-end localization method that synergistically integrates FM signals with wavelet transform and Swin Transformer, aiming to enhance localization accuracy by extracting deeper features from FM signals. To validate the efficacy of the proposed method, a comprehensive dataset was constructed, and a series of experiments were conducted to compare the performance of existing localization methods against the proposed approach. The experimental results demonstrate that, in various complex environments, the proposed method outperforms traditional RSS-based localization techniques in terms of both localization accuracy and stability.