Drogue detection algorithm in visual navigation system for autonomous aerial refueling

Drogue detection is important for relative navigation system for probe-and-drogue autonomous aerial refueling. It is a challenging task to detect the drogue with random motion due to disturbances caused by both the tanker wake vortex and atmospheric turbulence. In this paper, the problem of drogue detection was considered as moving object detection. A method based on multi-scale low rank and sparse decomposition was proposed for drogue detection. Firstly, the image sequences were decomposed by stationary wavelet transform respectively. Then the object in the low frequency sub-band image sequences of coarse scale was used as object confidence map to feedback the low sub-band image sequences of next fine scale for low rank and sparse decomposition. The experimental results show that the proposed algorithm is effective for drogue detection in real autonomous aerial refueling data.