Reconstruction of Signal Using Least-Square Method for Multi-functional Sensor

摘要

A least mean squares technique has been used to realize the measurand evaluation from sparse calibration data. While using this method, to obtain a best space for linearity approach (BSLA), an optimal solution is set up to process the redundant measurement data, which improves the measurement reconstruction under the circumstance of three-dimension cases while the sensors often have three or more measurement functions. An emulation circuit is also presented, as well as the simulation results and error analysis.