Self-Calibration Algorithm and FPGA Implementation for Data Acquisition

Due to the no ideal characteristics of devices, the impacts of temperature and environment noise, linear conversion errors exist in common Data Acquisition Systems (DAS). In most applications, the acquired data need to be calibrated to satisfy the accuracy and real-time requirements of the system. However, conventional calibration methods are based on software and specialized devices are not appropriate for high-speed real-time systems. In this paper, a FPGA-based self-calibration method is presented. This method employs a pipeline structure, solves the problems of hardware division and adaptive selection of calibration parameters, and implements real-time mean filtering and adaptive calibration of the data. Experiment results show that the proposed method can be used on a DAS to improve its accuracy and real-time performance.