针对视觉式头部姿态跟踪数据带有时变噪声的问题, 设计了一种基于数据融合的座舱头部姿态跟踪方法。其根据空间点与图像点的对应关系, 先利用正交迭代算法求解PNP问题, 然后应用Sage-Husa自适应滤波代替EKF解决时变噪声的问题, 最后使用线性加权的航迹融合算法对Outside-in跟踪和Inside-out跟踪输出的头部姿态进行数据融合来获取精度更加稳定的头部姿态。利用经验数据做了一系列的仿真, 结果显示该系统的跟踪精度有很大提高并且稳定可靠。

Aiming at the problem that the tracking data of visual head posture tracker involve time-varying noise, a method for cockpit head posture tracking based on data fusion is designed. According to the corresponding relationship between the space points and image points, orthogonal iteration algorithm is used at first to solve PNP problem. Then, the problem of the time-varying noise is solved by using Sage-Husa adaptive filter instead of EKF. Finally, a linear weighted fusion algorithm is used to fuse head posture data of the Outside-in tracker and Inside-out tracker to obtain head posture with more stable accuracy. Empirical data are used in a series of simulation, the results show that the tracking accuracy of the system is greatly improved and the system is stable and reliable.