As a guide rail is the basic motion unit of precision equipment, the measurement of and compensation for its motion errors are important preconditions for precision machining and manufacturing. A targetless and simultaneous measurement method of three-degree-of-freedom (3-DOF) angular motion errors using digital speckle pattern interferometry (DSPI) is introduced in this paper. Based on the analysis of the sensitivity mechanism of DSPI to DOF errors and the formation mechanism of the phase fringes, the relationship between the angular motion errors and the distribution of the interferometric phases was established, and a new simultaneous measurement model of 3-DOF angular motion errors was further proposed. An optical setup based on a three-dimensional spatial-carrier DSPI with a right-angle symmetrical layout was used in the measurement system. Furthermore, repetitive tests, noise tests, and precision analysis were carried out to verify the performance of the system. The test results showed that the measurement resolution of the system was <1 μrad, which is capable of measuring the pitch angle, yaw angle, and roll angle at the submicron arc level simultaneously without target mirrors. The method has the advantages of no need to install cooperative targets and high measurement resolution, showing broad application prospects in many fields, including mechanical manufacturing, laser detection, aerospace, etc.

Biomimetic vision is a promising method for efficient navigation and perception, showing great potential in modern navigation systems. Optical flow information, which comes from changes in an image on an organism’s retina as it moves relative to objects, is crucial in this process. Similarly, the star sensor is a critical component to obtain the optical flow for attitude measurement using sequences of star images. Accurate information on angular velocity obtained from star sensors could guarantee the proper functioning of spacecraft in complex environments. In this study, an optimized Kalman filtering method based on the optical flow of star images for spacecraft angular velocity estimation is proposed. The optimized Kalman filtering method introduces an adaptive factor to enhance the adaptability under dynamic conditions and improve the accuracy of angular velocity estimation. This method only requires optical flow from two consecutive star images. In simulation experiments, the proposed method has been compared with the classic Kalman filtering method. The results demonstrate the high precision and robust performance of the proposed method.