A Study on Multi-sensor Data Fusion Algorithm

Abstract

As an important research direction in the field of sensors, multi-sensor data fusion has received greater attention and development in areas such as robotics and autonomous driving. This paper provides a comprehensive introduction to the physical model-like and parameter-based data fusion algorithms that are often used in current engineering. Meanwhile, the process, steps and recent developments of the weighted average method and the extended Kalman filter method are highlighted, and multi-sensor data fusion experiments are conducted for each of the two algorithms. The simulation results prove that the data fusion algorithm has a good fusion effect.