CAJ | 학술논문

由于大气密度、气动参数、突风和沙尘暴等因素的影响，火星探测器在进入段高速飞行的动力学模型中往往带来未知输入，这些未知输入使传统的滤波方法出现较大的偏差。研究采用一种新的自校准扩展 Kalman滤波方法，对火星进入段的探测器进行状态估计，可以成功地消除这些未知输入带来的影响。数值仿真结果表明，该方法能有效提高导航精度。
유우대기밀도、기동삼수、돌풍화사진폭등인소적영향，화성탐측기재진입단고속비행적동역학모형중왕왕대래미지수입，저사미지수입사전통적려파방법출현교대적편차。연구채용일충신적자교준확전 Kalman려파방법，대화성진입단적탐측기진행상태고계，가이성공지소제저사미지수입대래적영향。수치방진결과표명，해방법능유효제고도항정도。
There always are unknown inputs in the dynamic model of high-speed Mars vehicle during the Mars entry phase because of the atmospheric density,aerodynamic parameters,gust and sand storm,etc.Due to the effect of the unknown inputs,the traditional filtering methods may produce greater errors.This paper estimates the states of the Mars entry vehicle by using a new self-calibration extended Kalman filter,and successfully eliminates the effect of the unknown inputs.Numerical simulation shows that this self-calibration method may effectively improve navigation accuracy.