Data Processing and Fusion Working Mechanism Scheme of MIMU Sensor Network

Abstract

Aiming at the engineering environment that requires a wide range of laying, long working hours, high accuracy and reliability, a sensor network framework model was proposed, which can effectively acquire the collected information and meet the real-time data transmission function. At the same time, a data processing and fusion scheme was proposed to remove trend and gross error terms from the static collected data. The trend test and ADF test data are used to meet the stability requirements. Then a multi-redundancy data fusion mechanism is applied for data fusion of preprocessed data. Finally, via the Allan variance method, the random noise characteristics of the gyro was analyzed, and the data quality and fusion effect are evaluated. Experimental results show that the designed sensor network can effectively collect real-time information, and the data processing and fusion working mechanism can effectively reduce noise and improve data quality.