This study aims to assess the autonomous navigation performance of an asteroid orbiter enhanced using an inter-satellite link to a beacon satellite. Autonomous navigation includes the orbit determination of the orbiter and beacon, and asteroid gravity estimation without any ground station support. Navigation measurements were acquired using satellite-to-satellite tracking (SST) and optical observation of asteroid surface landmarks. This study presents a new orbiter-beacon SST scheme, in which the orbiter circumnavigates the asteroid in a low-altitude strongly-perturbed orbit, and the beacon remains in a high-altitude weakly-perturbed orbit. We used Asteroid 433 Eros as an example, and analyzed and designed low- and high-altitude orbits for the orbiter and beacon. The navigation measurements were precisely modeled, extended Kalman filters were devised, and observation configuration was analyzed using the Cramer-Rao lower bound (CRLB). Monte Carlo simulations were carried out to assess the effects of the orbital inclination and altitudes of the orbiter and beacon as key influencing factors. The simulation results showed that the proposed SST scheme was an effective solution for enhancing the autonomous navigation performance of the orbiter, particularly for improving the accuracy of gravity estimation.

The classical interactive multimodel (IMM) algorithm has some disadvantages in tracking a noncooperative continuous thrust maneuvering spacecraft, such as poor steady-state accuracy, difficult selection of subfilter parameters, and mismatched model jump. To address the abovementioned problems, a variable-dimensional adaptive IMM strong tracking filtering algorithm (VAIMM-STEKF) is proposed to estimate the spacecraft’s position, velocity, and maneuvering acceleration state. VAIMM-STEKF contains 2 models, model 1 and model 2, which correspond to the tracking of the spacecraft in maneuvering and nonmaneuvering situations. Model 1 estimates the position and velocity of the spacecraft to ensure tracking accuracy when no maneuver occurs. Model 2 is a strong tracking filter with an augmented state. The adaptive IMM algorithm adjusts the fixed Markov transfer matrix in real time according to the model output probability. According to the different states of the spacecraft, the corresponding model interactive fusion method, together with the strong tracking filter, is adopted to ensure fast tracking when the spacecraft state changes. This method can also adapt to continuous thrust maneuvering spacecraft with different orders of magnitude. Simulation results show that the position accuracy of VAIMM-STEKF can be improved by approximately 27% and the speed accuracy can be enhanced by approximately 17% under different levels of maneuvering acceleration compared with those of the IMM algorithm. The convergence speed of VAIMM-STEKF is also better than the IMM algorithm.