基于FPGA的深空图像实时边缘检测算法与实现

航天器的导航控制是深空探索的重要关键技术之一。随着探索距离越来越远,传统地面站控制的局限性越发明显,因此航天器自主导航成为深空探索的发展方向。边缘检测是光学自主导航系统中定位天体目标的关键算法之一,为了满足星载计算机计算的实时性要求,文中提出了一种优化的Canny边缘检测算法和FPGA电路架构来优化Canny边缘检测算法中的非极大值抑制并采用动态单阈值,使其能够以较少的资源占用在FPGA上以流水线架构实现。该方法在保证边缘提取精度地前提下满足光学自主导航实时性的要求,对复杂的星体目标也具有较好的鲁棒性。

FPGA-Based Real-Time Edge Detection and its Implementation for Deep-Space Images

Navigation control of spacecraft is one of the key technologies in deep space exploration. However, As the exploration distance is getting farther, the limitations of traditional ground station control become more obvious. Therefore, autonomous optical navigation has become the development direction of aerospace exploration in the future. The edge detection technology is one of the critical algorithms in optical autonomous navigation. In order to meet the real-time requirement of on-board computing, this study proposed an optimized Canny edge detection algorithm and the circuit architecture of FPGA to optimize the non-maximum suppression and adopt dynamic single threshold of Canny edge detection algorithm. In this way, it could be implemented on the FPGA with less resource occupation and pipeline architecture. Finally, the real-time requirement of optical autonomous navigation was satisfied on the premise of guaranteeing the accuracy of edge extraction. and it had good robustness to complex star targets.