非合作目标视觉/惯导相对导航及敏感器自标定方法

利用视觉/惯导对空间非合作目标进行相对导航时,两敏感器的外参数对导航精度有较大影响。考虑到敏感器间的外参数标定复杂且耗时,提出一种利用视觉/惯导在估计相对状态过程中对其外参数进行标定的方法。该方法将视觉/惯导的外参数作为状态变量,与相对轨道运动学方程、相对姿态方程及惯导模型共同组成系统状态方程。利用该状态方程和单目视觉的观测量设计扩展卡尔曼滤波器对相对位姿、惯导偏差及视觉/惯导外参数进行估计,并通过数学仿真对该方法的有效性进行验证。仿真结果表明,该方法能够在视觉/惯导初始外参有偏差的情况下,有效估计相对位姿及惯导漂移,并对视觉/惯导外参数进行标定。

Method of vision/inertial relative navigation for non-cooperative target and sensors self-calibration

When using the combination system with visual and IMU (Inertial Measurement Unit) to estimate the relative pose of non-cooperative target in space, the external parameters of the system had a great influence on the estimation accuracy. Considering the complex and time-consuming calibration of the external parameters, this paper presented a method to estimate the relative pose and calibrate the external parameters simultaneously by using visual and IMU combination system. This method took the external parameters as the state variables and formed the system state equation together with the relative orbital kinematics equation, the relative attitude equation and the IMU model. Then, the relative pose, IMU biases and external parameters of the visual and IMU were estimated by using the Extended Kalman Filter designed with the state equation and the observation of the monocular vision. Finally, the validity of the method was verified by mathematical simulation. The simulation results showed that this method could estimate the relative pose and IMU biases effectively and calibrate the external parameters, when the deviation of external parameters existed.