复杂干扰环境下基于频域Gabor滤波和相关滤波的空中目标跟踪算法

Aerial infrared target automatic tracking technology is the core technology of the photoelectric countermeasure system of infrared imaging missiles. Aiming at challenging conditions of complex battlefield environment, large scale change of air target, infrared interference partial occlusion and so on, we propose a new correlation filtering algorithm based on Gabor filtering features in the frequency domain for aerial infrared target tracking. This algorithm constructs a set of frequency-domain Gabor filters, which extracts frequency-domain Gabor filtering(GF) features of the target image block and reduces dimension fusion, thereby effectively suppressing background noise and highlighting target texture information. According to the characteristics and variation law of spectrum energy distribution, the eigenvectors of target spectrum scale are extracted to improve the accuracy of target scale information estimation. High-confidence patches are used to track the reliable part of the target, and the energy distribution of the tracking box is calculated to predict the occluded part of the target simultaneously. This method provides more target information and improves the robustness of the algorithm in case of reappearance of the occluded target. Compared with other tracking algorithms, the average accuracy of the proposed algorithm was improved by 15.2%, and the frame frequency reached above 110 Hz.