Small UAV Target Detection Model Based on Deep Neural Network

Abstract

Unmanned aerial vehicle (UAV) has relatively small size and weak visual characteristics. The recognition accuracy of traditional object detection methods can decrease sharply when complex background and distraction objects exist. In this paper, we proposed a novel deep neural network (DNN) model for small UAV target recognition task. Based on the visual characteristics of surveillance image and UAV target, a multi-channel DNN is designed. Training and optimization of the DNN are completed with self-constructed UAV image database. Simulation results show that the proposed DNN model can achieve good results in recognizing the variable-scale UAV target and have compatible performance in distinguishing the interference and that the proposed model is robust and has a great potential prospect for engineering application.