We present UWSPSM, an algorithm of uncertainty weighted stereopsis pose solution method based on the projection vector which to solve the problem of pose estimation for stereo vision measurement system based on feature points. Firstly, we use a covariance matrix to represent the direction uncertainty of feature points, and utilize projection matrix to integrate the direction uncertainty of feature points into stereo-vision pose estimation. Then, the optimal translation vector is solved based on the projection vector of feature points, as well the depth is updated by the projection vector of feature points. In the absolute azimuth solution stage, the singular value decomposition algorithm is used to calculate the relative attitude matrix, and the above two stages are iteratively performed until the result converges. Finally, the convergence of the proposed algorithm is proved, from the theoretical point of view, by the global convergence theorem. Expanded into stereo-vision, the fixed relationship constraint between cameras is introduced into the stereoscopic pose estimation, so that only one pose parameter of the two images captured is optimized in the iterative process, and the two cameras are better bound as a camera, it can improve accuracy and efficiency while enhancing measurement reliability. The experimental results show that the proposed pose estimation algorithm can converge quickly, has high-precision and good robustness, and can tolerate different degrees of error uncertainty. So, it has useful practical application prospects.

A finite-time extended, state-observer-based, fixed-time backstepping control algorithm was designed for hypersonic flight vehicles. To enhance the robustness of the controller, two novel finite-time extended state observers were introduced to compensate for the negative effects of lumped disturbances such as uncertainties and external disturbances. Two hyperbolic sine tracking differentiators were used to approximate the derivatives of the virtual control signals and guidance commands, thereby alleviating the computational burden associated with traditional backstepping control. Furthermore, a fixed-time backstepping attitude controller was used to guarantee that the tracking errors converged to a small neighbor of the origin in fixed time. According to the simulation results, the proposed controller outperformed a fixed-time sliding mode disturbance, observer-based, finite-time backstepping controller in terms of the tracking precision and convergence rate. Moreover, the proposed controller was noted to be robust in simulations involving lumped disturbances.