B-Spline Approximation Using an EKF for Signal Reconstruction of Nonlinear Multifunctional Sensors

In this paper, a novel method based on a B-spline approximation and the extended Kalman filter (EKF) is proposed for the signal reconstruction of nonlinear multifunctional sensors. The B-spline approximation is a very effective and conventional tool for nonlinear modeling. However, the computation of the B-spline control array by the least square method is very complex for implementation on microprocessors. Therefore, the EKF, which is a suboptimal recursive filter, is proposed to compute the control array with high accuracy and a low hardware requirement. Experiments are performed to reconstruct the measurands of a two-input-two-output circuit model and a real three-input-two-output multifunctional sensor. Results show that the proposed method provides a good solution to the signal reconstruction of multifunctional sensors.