基于序列图像的深空小天体探测自主相对导航误差补偿方法研究

Autonomous relative navigation error compensation method for small body exploration based on sequence-images

深空小天体是典型的空间非合作目标.基于序列图像的空间非合作目标自主相对导航是实现小天体探测的重要技术手段.由于在轨环境复杂,相机不可避免地会出现测量偏差,进而影响相对导航状态估计精度.本文在充分利用相机视场内恒星序列图像的基础上,通过最小二乘法计算相机在轨标定初值,结合测量偏差状态转移模型和"恒星对"之间的星光角距测量方程,将测量偏差扩维成状态估计参数,构建了基于相机在轨误差补偿的相对导航状态估计模型.结合无迹卡尔曼滤波算法,通过序列图像的帧间信息对比进行迭代估计,获得相机测量偏差和相对导航系统状态,提高状态估计精度.仿真分析中采用2016HO3小天体作为相对导航目标,仿真结果说明了该方法的有效性,能够有效地补偿相机测量偏差,实现相对导航系统状态高精度估计,为后续开展相关任务提供了一定的技术支撑.

Deep-space small bodies are typical space non-cooperative targets. The autonomous relative navigation of space noncooperative targets based on sequence-images is an important technical method to realize the small body exploration.Due to the complex on-orbit environment, it is inevitable that the camera will suffer the measurement deviations and the focal length deviation, which will severely affect the relative navigation state estimation accuracy. On the basis of making full use of the information of star sequence images in the field of view of the camera, the initial value of the camera onorbit calibration is calculated by the least square method. Combined with the measurement deviation state transition model and the starlight angular distance measurement equation between two stars, the measurement deviations are expanded into state estimation parameters and the relative navigation state estimation model based on camera on-orbit error compensation is constructed. Combined with the unscented Kalman filter algorithm, the iterative estimation is carried out through comparing the information between the frames of sequence images. Then the camera measurement deviation and the relative navigation system state are obtained. In this way, the state estimation accuracy is improved. In the simulation analysis, the small body 2016 HO3 is considered as the relative navigation target. The simulation results show the effectiveness of the method, which can effectively compensate the camera measurement deviation and achieve the high-precision estimation of the relative navigation system state. The research results provide certain technical support for the subsequent related tasks.