Aerial Target Tracking Based on Frequency-Domain Gabor Filters and Correlation Filters under Complex Interference Environment

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

School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China

Received: 26 March 2020

Abstract

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.

摘要

空中红外目标自动跟踪技术是红外成像导弹光电对抗系统的核心技术，针对复杂战场环境、空中目标大尺度变化、红外干扰部分遮挡等挑战性情况，提出了一种基于频域Gabor滤波的相关滤波空中红外目标跟踪算法。该算法构造一组频域Gabor滤波器组，对目标图像块进行频域Gabor滤波特征(简称GF特征)提取、降维融合，有效抑制背景噪声、突出目标纹理信息；根据频谱能量分布特点及变化规律，提取目标频谱尺度、旋转特征向量，提升目标尺度信息估计的准确性；利用高置信分块跟踪目标可靠部位，提升算法鲁棒性。相比于其他跟踪算法，该算法平均精确度评价提高15.2%，帧频达到110 Hz以上。