二维最大熵和椭圆匹配的月面障碍物识别

Lunar surface hazard detection by 2D maximum entropy thresholding and ellipse fitting

月面障碍物识别是月球探测器自主着陆末段一个非常重要的环节.而岩石是月球表面存在较多的一种地理特征,有效地识别岩石既可以保证月球探测器的安全着陆,也可以为探测器选择适合巡视勘查的着陆场提供必要的信息.研究中将二维最大熵方法应用于图像分割,获得图像中由障碍物形成的阴影区域,然后使用椭圆匹配的方法匹配岩石的阴影区域,获得岩石的尺寸和位置.仿真实验结果表明,该算法可在0.3 s内有效地识别出图像中直径0.1 m以上的各种尺寸岩石,符合月球探测器末制导任务的实时性和精确性要求.

Hazard detection is a very important operation in the final phase of a soft landing on the moon. Since rock is one of the geographical features of the lunar surface, effective identification of rocks can not only guarantee the safety of the landing, but can also provide necessary information for further exploration after landing. To seg- ment the shadow region from the image, a two-dimensional maximum entropy method was proposed. An ellipse fitting algorithm was then used to estimate the sizes and locations of rocks. Simulations demonstrated that these meth- ods can effectively detect rocks with diameters larger than 0.1 m in an image, and the whole operation takes less than 0.3 s.