2results about How to "Avoid flight accidents" patented technology

This invention provides an unmanned aerial vehicle (UAV) image transmission system and image transmission method. The system includes: a radio frequency (RF) transceiver, a balanced amplifier circuit, a low-noise amplifier, and an RF switch. The balanced amplifier circuit includes at least two parallel power amplifiers configured to superimpose the amplified signals from each power amplifier in phase to synthesize the output power. The RF transceiver generates a time-division duplex control signal to synchronously control the switching of each component between transmit and receive modes. By employing a balanced amplifier circuit, this invention enables each power amplifier to operate in a region with better linearity, thereby improving transmit power while ensuring the signal quality required for high-order modulation, thus balancing long-distance transmission and high-definition image quality.

The invention relates to the field of airport road foreign matter detection, and provides a machine learning-based FOD detection algorithm, which comprises an input module used for receiving basic image data of an airport runway; the processing module is used for carrying out preprocessing and feature extraction on the input data; the storage module is used for storing the original image data and the detection result; the acquisition module is used for acquiring image and sound data of an airport runway in real time; and the recognition module is used for recognizing moving objects and static objects in the collected data based on a machine learning model. And high-precision real-time detection is realized through cooperation of multiple modules. The acquisition module adopts a high-definition camera to ensure that image data is clear; the processing module utilizes a convolutional neural network (CNN) to extract features, and can accurately recognize moving and static objects in combination with a YOLOv5 algorithm of the recognition module. The comparison module compares the real-time image with the original image, abnormity is judged if the real-time image is lower than the threshold value, the runway foreign matter can be found in time, and the system can rapidly position the FOD in the complex environment.