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Regarding the relative detection of the moving direction in vertical between the unmanned aerial vehicle (UAV) and the ground target, we have been inspired by the functional advantages of flying insects in nature, such as lightweight, low computational complexity, low power, and the natural characteristics of high adaptability and high reliability in the detection and tracking or escape process of targets. Based on this, with the help of LGMD (lobula giant movement detector) neuron modeling, this paper proposes a detection model of the moving direction in vertical for UAV ground infrared targets based on LGMD neurons modeling (referred to as LGMD-UAVGIT model). In this paper, experiments and tests are mainly carried out on infrared imaging videos taken by UAVs, thus verifying the effectiveness of the new model proposed in the paper for detecting the two typical vertical movement directions of UAVs that are relatively far away from and close to the ground targets.

A Detection Model of the Moving Direction in Vertical for UAV to Search Ground Infrared Targets