Virginia Patent of the Month – July 2025
A new patent awarded to DeepSig Inc. introduces an innovative approach to radio signal detection. The technology uses machine learning to automatically find and classify signals. This could improve the efficiency of spectrum enforcement and security. U.S. Patent No. 12373715, titled ‘Radio frequency band segmentation, signal detection and labelling using machine learning’, details the new system. It processes radio frequency data with speed and accuracy. The system trains a model to detect and label signals in real-time. This is a big step for managing complex radio environments.
Advanced Signal Analysis
The patented method receives electromagnetic energy from a receiver. It then examines this energy to detect signals. It transforms signals from a time-series representation to a time-frequency representation. This creates a visual map. A machine learning model analyzes this map. It determines the boundaries of each signal. It also classifies the signal’s type. This process is very fast and efficient. It can improve detection accuracy. This reduces false positives and negatives.
Real-World Applications
The technology can be used in many industries. For example, a telecommunications company can map 5G coverage. It can quickly detect interference. It can also find unauthorized base stations. The system is small and portable. It can be mounted on vehicles, aircraft, or drones. This allows for mobile data collection. The innovation could also be used for defense applications. It can detect communication systems and electronic warfare. This makes it part of a rapid warning system.
Training for Versatility
DeepSig’s method uses a unique training system. It augments radio signals with simulated impairments and noise. This creates a large, diverse dataset. The model learns to perform well in various environments. It works with different hardware and radio settings. This reduces the need for extensive real-world data collection. The training process helps the model generalize effectively. This makes it highly adaptable. It can be deployed to different radio systems and geographical areas.
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