Optimal Maneuvering for Autonomous Relative Navigation Using Monocular Camera Sequential Images

The use of monocular sequential images for relative navigation provides an efficient method for estimating the relative state of space non-cooperative targets, where the estimation accuracy is important to the relative navigation mission. A one-step optimal maneuver solution method is proposed that improves the state estimation accuracy. To determine the optimal maneuver and realize high-accuracy relative navigation, the relationship between the entire process of state estimation accuracy and the one-step maneuver is derived as an analytical model through the Fisher information matrix. An optimization problem is constructed and the one-step optimal maneuver is obtained in consideration of fuel constraints, the position constraints, the anticollision conditions and the observability conditions based on the state estimation accuracy analytical model combined with practical engineering requirements. The simulation results indicate that optimal maneuvering can effectively improve the state estimation accuracy, and they illustrate that the fuel constraint is a significant factor. Thus, the fuel constraint can be modified to produce better system state estimation accuracy with a certain range. When the fuel constraint reaches a certain level, the state estimation accuracy attains a stable value.