Abstract As various infrared countermeasures have been developed, aerial infrared target tracking is becoming increasingly challenging. In this paper, we develop an algorithm that can reliably track fighter in the case of severe infrared jamming. Since most parts of the target are obscured by a decoy, we propose an algorithm that can track a fighter by detecting its visible components rather than the whole target. Inspired by the human skeletal model of the Microsoft Kinect sensor, a skeletal model of a fighter comprising three components is designed. Then, a detection method based on Cascade R-CNN is used to detect those components. Situation assessment is made based on the detection result. As a result, the position of the target can be estimated through the detection result and skeletal model. We evaluated this proposed approach on an infrared image dataset against six state-of-the-art trackers. The experimental results demonstrate that our algorithm can reliably track a fighter in severe infrared jamming while running at a fast speed of 11.2 FPS.

中文翻译：

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基于骨骼跟踪技术的重度干扰下航空红外目标跟踪

摘要 随着各种红外对抗手段的发展，空中红外目标跟踪变得越来越具有挑战性。在本文中，我们开发了一种算法，可以在严重红外干扰的情况下可靠地跟踪战斗机。由于目标的大部分部分都被诱饵遮挡了，我们提出了一种算法，可以通过检测其可见部分而不是整个目标来跟踪战斗机。受微软 Kinect 传感器人体骨骼模型的启发，设计了一个由三部分组成的战斗机骨骼模型。然后，使用基于 Cascade R-CNN 的检测方法来检测这些组件。根据检测结果进行情况评估。因此，可以通过检测结果和骨骼模型来估计目标的位置。我们针对六个最先进的跟踪器在红外图像数据集上评估了这种建议的方法。实验结果表明，我们的算法可以在11.2 FPS的高速运行下可靠地跟踪受到严重红外干扰的战斗机。