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Autonomous navigation to quasi-periodic orbits near translunar libration points

Chinese Journal of Aeronautics 2013年第5期26卷 1259-1268页

作者： Jing Wuxing Qian Yingjing Gao Changsheng Li Jianqing Department of Aerospace Engineering Harbin Institute of Technology

Libration-point missions have been very useful and successful. Due to the unstable natures of most of these orbits, the long-time stationkeeping demands frequent maneuvers and precise orbit determinations. Earth-based tracking will have to undertake much more responsibilities with the increasing number of libration missions. An autonomous navigation system could offer a better way to decrease the need for Earth-based tracking. Nevertheless, when an autonomous navigation system is applied, there are three important factors affecting autonomous navigation accuracy, i.e., the accuracy of initial conditions, the accuracy of measurements, and the accuracy of onboard dynamics for propagation. This paper focuses on analyzing the influence from the third factor and finding an appropriate navigation dynamics, which can satisfy the requirement of estimation accuracy but not cause too much burden for onboard computation. When considering the restricted three-body model and the bicircular restricted four-body model as navigation dynamics, the astrin- gency is not shown during the simulations. Meanwhile, when considering the influences of the Sun＇s direct and indirect perturbations and the eccentricity of the Moon＇s orbit, a new navigation dynamic model with the standard ephemerides is proposed. The simulation shows the feasibility of the proposed model.

关键词： Autonomous navigation extended kalman filters Libration points Multi-body dynamics Quasi-periodic orbit

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Robust extended kalman filter with input estimation for maneuver tracking

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Chinese Journal of Aeronautics 2018年第9期31卷 1910-1919页

作者： Yuzi JIANG Hexi BAOYIN School of Aerospace Engineering Tsinghua University

This study investigates the problem of tracking a satellite performing unknown continuous maneuvers. A new method is proposed for estimating both the state and maneuver acceleration of the satellite. The estimation of the maneuver acceleration is obtained by the combination of an unbiased minimum-variance input and state estimation method and a low-pass filter. Then a threshold-based maneuver detection approach is developed to determinate the start and end time of the unknown maneuvers. During the maneuvering period, the estimation error of the maneuver acceleration is modeled as the sum of a fluctuation error and a sudden change error. A robust extended kalman filter is developed for dealing with the acceleration estimate error and providing state estimation. Simulation results show that, compared with the Unbiased Minimum-variance Input and State Estimation(UMISE) method, the proposed method has the same position estimation accuracy, and the velocity estimation error is reduced by about 5 times during the maneuver period. Besides, the acceleration detection and estimation accuracy of the proposed method is much higher than that of the UMISE method.

关键词： extended kalman filters Input estimation Maneuver detection Maneuver tracking Orbit determination

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维普期刊数据库

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Several Methods of Radar Data Fusion 3

Several Methods of Radar Data Fusion

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2002 3rd International Symposium on Electromagnetic Compatibility

作者： XU Yu JIN Yihui ZHOU Yan Automation Department of TsingHua University

ISBN: (纸本)0780372778

＜正＞In the processing of radar data,target estimation states fusion is an important *** under the decentralized model,various estimations of target state which come from local filters with kalman filter will been fused in order to obtain more accurate target estimation *** are two problems should been *** one is fusion criteria,different fusion criteria will bring out different *** fusion criteria have been discussed in this paper,one is based on the covariance matrix of estimation error and the second is depended on the infinite normal number,the last is related to element of state vector;The second problem is tracking algorithm,it will affect the accuracy of state fusion *** this paper three criteria and their corresponding algorithms have been *** algorithms estimate target state are set up with the strong tracking filter other than kalman or extended kalman filter,they have better tracking performance so that they can overcome the shortages related to kalman or extended kalman *** will be explained in the *** last the compare results have been given.

关键词： extended kalman filters

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