In this work, an orbit determination algorithm suitable for CubeSats onboard implementation is developed, which simulates optical autonomous navigation accomplished by a stand-alone platform. An extended Kalman filter featuring line-of-sight acquisitions of planets is selected as the state estimator, and its performances are tested on a Raspberry Pi, whose characteristics are comparable to a miniaturized onboard computer. An improvement of the solution accuracy is performed by correcting the planetary light-time and aberration effects as well as by exploiting the optimal beacons selection strategy to acquire the external observations. Moreover, the numerical precision of the estimator is improved through the implementation of factorization techniques and nondimensionalization strategies. The results are presented for a sample Earth–Mars transfer, where the time slot for the navigation campaign involves 2 h every 10 days. At final time, the probe position and velocity are estimated with a $3\sigma$ accuracy of 360 km and 0.04 m/s, respectively.

在这项工作中，开发了一种适用于 CubeSats 机载实施的轨道确定算法，该算法模拟了由独立平台完成的光学自主导航。选择具有行星视距获取的扩展卡尔曼滤波器作为状态估计器，并在树莓派上对其性能进行了测试，其特性可与小型机载计算机相媲美。通过校正行星光时和像差效应以及利用最佳信标选择策略来获取外部观测，来提高求解精度。此外，通过实施分解技术和无量纲化策略，提高了估计器的数值精度。给出了地球-火星转移样本的结果，其中导航活动的时间段涉及每 10 天 2 小时。在最后时刻，探针的位置和速度估计为$3\sigma$精度分别为 360 km 和 0.04 m/s。