Motion Tracking and Detection System Based on Motion Sensor

Abstract

To solve the problem of large error of motion MEMS sensor in motion trajectory detection, a motion trajectory tracking and detection system based on motion sensor is proposed. The principle of trajectory tracking is that the three-dimensional velocity and displacement can be obtained by integrating the acceleration. In this paper, acceleration sensor is used to obtain acceleration data of moving object. In order to reduce the data measurement error, a Kalman filter is designed and implemented to eliminate random noise. Aiming at the system nonlinear error, a two speed sampling compensation algorithm is designed and implemented by using the random characteristics of kernel process scheduling algorithm. The system accuracy is significantly improved without increasing the computational burden. According to the characteristics of floating-point instruction system on Advanced RISC Machine (ARM) platform, the algorithms of process core modules such as square root and matrix multiplication are optimized and improved, which greatly improves the computing performance of the system. According to the results of the study, the average error of measurement of X-line displacement measurement of the space control system is 8.06%, the average error of measurement of Y-line displacement measurement is 7.41%, the average error of measurement of Z-line displacement measurement is 9.61%, and the average error of 3D dimensional measurement is 7.6%. The effectiveness and feasibility of the system are verified.