URGENT UPDATE: A groundbreaking recognition method for underwater communication signals that mimic dolphin whistles has just been announced by researchers from Tianjin University and the Shenyang Institute of Automation. This innovative technology aims to enhance covert communication capabilities in maritime military operations, overcoming significant challenges faced by conventional recognition methods.
Traditional underwater communication systems struggle with signals designed to be discreet, often misclassifying them as background noise. The new method utilizes a convolutional neural network (CNN) to accurately identify these signals, achieving a remarkable 90% recognition accuracy in simulations at a signal-to-noise ratio (SNR) of 0 dB. Such advancements are critical as they provide military forces with improved communication strategies that are less detectable by adversaries.
The research, led by Qingwang YAO and his team, consists of three core steps to ensure effective recognition of continuously varying carrier frequency-modulated signals (CVCFMS) that mimic dolphin whistles. The process begins with Spatial Diversity Combining (SDC) to enhance the main signal while reducing interference from multiple paths, a common issue in underwater environments.
Next, the team employs a Time-Frequency Spectrum (TFS) Mask Filtering technique, treating the TFS as a 2D image to extract whistle signals from noisy settings. This method effectively filters out noise, allowing for clear identification of desired signals amidst distractions, which is essential for operational success.
Finally, the researchers apply the Phase Derivative Spectrum along with CNN recognition. By using the Hilbert transform and continuous wavelet transform (CWT), they generate a scalogram image that serves as input for the CNN, allowing for precise signal recognition. This sophisticated approach has shown to be particularly effective in deep-water channels, where interference is minimized.
Recent experiments conducted at Qingnian Lake in Tianjin confirmed the method’s effectiveness, achieving an 81% recognition accuracy over a distance of 150 meters and an SNR of 6.36 dB. This performance, while slightly lower than simulation results, demonstrates the method’s real-world applicability and potential for military and scientific use.
This breakthrough could revolutionize underwater communication, providing a vital tool for naval operations and enhancing the safety and efficiency of maritime missions. The implications for national security and environmental research are profound, making it essential for stakeholders to monitor these developments closely.
As the research community continues to evaluate and refine this method, further updates are expected, particularly regarding its implementation in active military settings. Keep an eye on this space for the latest advancements in underwater communication technologies.
For more detailed information, access the full text of the study titled “Recognition method for underwater communication signals that mimic dolphin whistles using phase-shifting modulation” [here](https://doi.org/10.1631/FITEE.2400572).
