Target Tracking Method Based on Information Matrix for Multi-sensor Data Fusion

Smart driving technology has great potential to improve traffic safety, traffic efficiency, and driving experience. So, it is a hot topic for current and future research in the field of intelligent transportation. However, the future advanced driver assistance system will contain multiple sensors for multiple applications, and the sensors are usually asynchronous and their data may be disordered, which makes the fusion of sensor data very important. In this paper, a multi-sensor vehicle tracking fusion method based on information matrix fusion is proposed. The problem of correlation between sensor data due to common process noise and common trajectory history is solved by the method, thus the need to replace global trajectory estimates with fused local estimates at each fusion cycle is eliminated, and the problem of easy scattering of filters due to unknown external environment is improved.