A Method for Detecting Non-Cooperative Communication Signals Utilizing Multi-Resolution Time-Frequency Images

Non-cooperative communication detection is a key technology for locating radio interference sources and conducting reconnaissance on adversary radiation sources. To meet the requirements of wide-area monitoring, a single interception channel often contains mixed multi-source signals and interference, resulting in generally low signal-to-noise ratio (SNR) of the received signals; meanwhile, improving detection quality urgently requires either high frequency resolution or high-time resolution, which poses severe challenges to detection techniques based on time-frequency representations (TFR). To address this issue, this paper proposes a fixed-frame-structure signal detection algorithm that integrates image enhancement and multi-scale template matching: first, the Otsu-Sauvola hybrid thresholding algorithm is employed to enhance TFR features, suppress noise interference, and extract time-frequency parameters of potential target signals (such as bandwidth and occurrence time); then, by exploiting the inherent time-frequency characteristics of the fixed-frame structure, the signal is subjected to multi-scale transformation (with either high-frequency resolution or high-time resolution), and accurate detection is achieved through the corresponding multi-scale template matching. Experimental results demonstrate that under 0 dB SNR conditions, the proposed algorithm achieves a detection rate greater than 87%, representing a significant improvement over traditional methods.