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Ning X.,Beihang University | Ning X.,Science and Technology on Inertial Laboratory and Fundamental Science | Liu L.,Beihang University | Fang J.,Beihang University | And 3 more authors.
Aerospace Science and Technology | Year: 2013

Navigation methods of lunar rovers like inertial navigation system (INS), dead reckoning and visual odometry must be provided with the initial navigation parameters such as initial position and attitude. The accuracy of these initial navigation parameters has a significant impact on the overall navigation accuracy. Taking INS as an example, on the Earth, initial position can be obtained from global positioning system (GPS) or other ground facilities, and initial attitude can be obtained through initial alignment. However, there is no GPS on the lunar surface, and the lunar rotation rate is too small to execute alignment. For solving this problem, a new initial position and attitude determination method based on INS/CNS (celestial navigation system) integration is presented in this paper. Star altitude error caused by the biases of accelerometers is considered and its corresponding measurement equation is established accurately for the first time. The horizontal velocity errors, starlight vectors and star altitudes are used to estimate the initial position and attitude by an unscented Kalman filter (UKF). Furthermore, the advantage of this new method is that the INS sensors errors can be estimated accurately. Semi-physical experiments show that higher estimation accuracy is achieved by this new method compared with that of the traditional INS alignment method and INS/CNS initialization methods. These results demonstrate that it is a promising and attractive method to provide the initial position and attitude for lunar rovers. © 2013 Elsevier Masson SAS. All rights reserved. Source

Ning X.,Beihang University | Ning X.,Science and Technology on Inertial Laboratory and Fundamental Science | Huang P.,Beihang University | Fang J.,Beihang University | And 4 more authors.
Acta Astronautica | Year: 2015

Celestial navigation (CeleNav) has been successfully used during gravity assist (GA) flyby for orbit determination in many deep space missions. Due to spacecraft attitude errors, ephemeris errors, the camera center-finding bias, and the frequency of the images before and after the GA flyby, the statistics of measurement noise cannot be accurately determined, and yet have time-varying characteristics, which may introduce large estimation error and even cause filter divergence. In this paper, an unscented Kalman filter (UKF) with adaptive measurement noise covariance, called ARUKF, is proposed to deal with this problem. ARUKF scales the measurement noise covariance according to the changes in innovation and residual sequences. Simulations demonstrate that ARUKF is robust to the inaccurate initial measurement noise covariance matrix and time-varying measurement noise. The impact factors in the ARUKF are also investigated. © 2015 IAA. Published by Elsevier Ltd. All rights reserved. Source

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