Adaptive Measurement of Space Target Separation Velocity Based on Monocular Vision

Spacecraft separation safety is the key characteristic of flight safety. Obtaining the velocity and distance curves of spacecraft and booster at the separation time is at the core of separation safety analysis. In order to solve the separation velocity measurement problem, this paper introduces the YOLOv8_n target detection algorithm and the circle fitting algorithm based on random sample consistency (RANSAC) to measure the separation velocity of space targets according to a space-based video obtained by a monocular camera installed on the spacecraft arrow-shaped body. Firstly, MobileNetV3 network is used to replace the backbone network of YOLOv8_n. Then, the circle fitting algorithm based on RANSAC is improved to improve the anti-interference performance and the adaptability to various light environments. Finally, by analyzing the imaging principle of the monocular camera and the results of circle feature detection, distance information is obtained, and then the measurement results of velocity are obtained. The experimental results based on a space-based video show that the YOLOv8_n target detection algorithm can detect the booster target quickly and accurately, and the improved circle fitting algorithm based on RANSAC can measure the separation speed in real time while maintaining the detection speed. The ground simulation results show that the error of this method is about 1.2%.