提出一种利用地球紫外波段和恒星可见光波段为卫星进行自主导航的方法, 该导航方法利用视场1观测恒星可见光波段, 视场2观测地球紫外波段。在视场1利用星敏感器全天球识别算法识别所有恒星星像, 识别结果的光轴指向作为恒星矢量; 视场2被用来对地球紫外波段轮廓成像, 计算得到地心矢量在卫星本体坐标系中的方向。最后, 利用卫星轨道动力学方程和扩展卡尔曼滤波器来计算卫星轨道参数。对一紫外敏感器进行的实验表明, 与利用红外地平仪和恒星可见光的自主导航方法相比, 该方法的位置误差由1 000 m减小到500 m, 速度误差由100 m/s减小到40 m/s, 而且消除了由于太阳光与地平线夹角带来的周期误差, 因此, 该方法具有很好的鲁棒性。

An autonomous navigation algorithm is proposed using the sensor with functions of a star sensor and an ultraviolet earth sensor. The sensor has two Field of Views (FOVs ) named FOV1 and FOV2. The FOV1 is used for star sensor and for calculating the optical axis direction of the FOV1. The FOV2 is used for ultraviolet earth sensor and for calculating the vector of the earth. The state equation of integrated system is established by the deduced orbit dynamic model based on orbit six elements and the attitude kinematic model. Then, the observed equation of integrated system is established by using the difference of the measurement value and the estimated value, and the satellite orbit parameters were calculated according to the Discrete Extend Kalman Filter(DEKF)algorithm. An experiment on the ultraviolet sensor shows that not only the errors of satellite positions is improved from 1 000 m to 500 m and the errors for satellite velocities are improved from 100 m/s to 40 m/s, but also the errors of periodic sine resulted from the angle between the sun light and ground level is eliminated. These results show the algorithm to be well robust.