Research Of Autonomous Optical Navigation Nonlinear Filtering Algorithm

In the new century, hot topics in deep space exploration are rising,which are represented by exploration missions of big and small celestial bodies. The new high tide of technology research and plan execution for deep space exploration have arrived.The communication delay induced by the large distance of deep space exploration is a long time.The communication of spacecraft and telemeter and command station on the ground can not satisfy with the need of deep space mission now.So deep space exploration autonomous navigation technology will replace it and will become a regarded key technology in the deep exploration fields.With the supports of Tenth Five-Year 863 Program (Autonomous Navigation Technology of Deep Spacecraft), this dissertation analyses the background and domestic and foreign situation of deep space exploration optical autonomous navigation. And the dissertation also studies the nonlinear filtering algorithms application in autonomous optical navigation technology.The main contents of this dissertation are as follows:First, based on the analysis of massive correlative valuable reference, this dissertation introduces the significance,background and domestic and foreign situation.Combined with the task flow of deep space and autonomous optical navigation, this dissertation briefly analyses the principle of optical navigation.To the different stage of deep space exploration, it introduces the relative orbit dynamics equations. And different autonomous optical navigation methods are proposed too.At the same time, observation equations of deep space exploration are introduced.So the well-grounded base is established for the next research work of autonomous optical navigation nonlinear filtering algorithm.Second, real-time performance is considered to be a main factor in deep space exploration fields. But large amount of data are more complex and time-consuming. At the same time, on-board computer's data processing is limited. To deal with these problems, cylindrical coordinate system is used in heliocentric ecliptic coordinate system in this dissertation. And TSS-EKF algorithm is applied in optical autonomous navigation too. They reduce the coupling between the state variables and the observation variables. Complex matrix operations are avoided too. And state estimation velocity is improved in the end. At the same time, the paper improves the approach stage relative dynamic model. Accuracy of dynamic model is improved to a certain degree. Combined with the approach stage dynamic model, UD-EKF algorithm is applied to autonomous navigation system. It is compared to EKF algorithm in this dissertation. And simulation results are far better than before.Finally, a particular problem is studied in the paper. That is many kinds of sensors used in the same system. The multisensor information fusion algorithm is introduced in optical autonomous navigation. To reduce the computational burden and to avoid the high-dimension computation and the large memory, the algorithm is improved by UD decomposition in this dissertation. So the convergence rate is improved. And besides, in order to analyze the impact of filter cycle on the observability of state equation, state equation's first order Taylor expansion is introduced in this dissertation. Feasibility was proved by the computer simulation.