CAJ | 학술논문

在光学辅助惯性导航系统中，观测信息的最优融合依赖于相机与惯性测量单元六自由度转换的精确校准。针对火星软着陆自主导航中的测量信息最优融合问题，提出了基于扩展卡尔曼滤波的导航敏感器相对位姿校准算法。该算法仅利用火星表面可获取的路标特征点信息，不借助额外的测量设备，对相机与惯性测量单元相对位姿进行精确的校准，同时，能够估计着陆器的位置、速度和姿态。考虑到着陆器机动和火星自旋的影响，建立了宽视场相机及惯性测量单元的高精度测量模型。最后通过数学仿真对所提出的校准算法的可行性和有效性进行了验证。
재광학보조관성도항계통중，관측신식적최우융합의뢰우상궤여관성측량단원륙자유도전환적정학교준。침대화성연착륙자주도항중적측량신식최우융합문제，제출료기우확전잡이만려파적도항민감기상대위자교준산법。해산법부이용화성표면가획취적로표특정점신식，불차조액외적측량설비，대상궤여관성측량단원상대위자진행정학적교준，동시，능구고계착륙기적위치、속도화자태。고필도착륙기궤동화화성자선적영향，건립료관시장상궤급관성측량단원적고정도측량모형。최후통과수학방진대소제출적교준산법적가행성화유효성진행료험증。
In the vision-aided inertial navigation system, optimal information fusion depends on accurate calibration of the six degrees-of-freedom transformation between a camera and an inertial measurement unit. Considering the measurement information optimal fusion problem of autonomous navigation during soft landing on Mars, a sensor-to-sensor relative pose calibration algorithm was proposed based on the extended Kalman filter. The proposed algorithm can accurately calibrate the relative pose of the camera and inertial measurement unit, and simultaneously estimate the position, velocity and attitude of the spacecraft. Moreover, obtaining this calibration information requires no additional measurement equipment except the landmark features on the surface of the Mars. Furthermore, high fidelity sensor models for wide field-of-view camera and inertial measurement unit were developed taking into account effects of the probe maneuver and the Mars rotation. Finally, the validity of the sensors calibration algorithm presented in this paper was demonstrated by mathematical simulation.