Low-small slow target photoelectric identification tracking method based on machine learning

Abstract

The invention designs a low-small slow target photoelectric identification tracking method based on machine learning. Firstly, the direction of the target is determined, and then the orientation angleand the pitch angle of the camera are adjusted so that the target is located in the field of view of the camera. Then the camera reads the image frame by frame, and the on-line detection of the target recognition is performed, the read image is taken as the input of the neural network. After machine learning, the trained network is complete to obtain the output of the network, including the classification of the target and the binding frame of the position. If the output classification belongs to the low small slow target, then go to the next step, otherwise skip the next step, directly readinto the next frame image, target tracking. While ensuring real-time performance, the accuracy of automatic recognition is improved, and the robustness to illumination, target posture and other factors is enhanced. The invention can be used for multi-band fusion imaging equipment, expands the application range of a single identification and tracking algorithm, and improves the adaptability of thealgorithm.

Description

technical field [0001] The invention belongs to the technical field of electromagnetic wave tracking systems other than radio waves, and in particular relates to a machine learning-based photoelectric identification and tracking method for low, small and slow targets. Background technique [0002] Low-altitude air strike weapons such as drones and cruise missiles are the main attack methods of current air strike operations, and drones also have the characteristics of low cost, light weight, small size, good maneuverability, and can perform tasks under dangerous conditions, making air defense systems The pressure has increased sharply, seriously threatening the safety and security work of major events and key areas. Detection is a necessary prerequisite for interception and strike, so the early warning and identification of low, slow targets such as drones is an important guarantee for air defense operations to seize the initiative in war under the conditions of future inform...

AI Technical Summary

Problems solved by technology

However, there is a lot of room for improvement in the robustness of these methods to factors such as illumination angles and target poses.

Images