Hongmian Du

A Group of Inverse Filters Based on Stabilized Solutions of Fredholm Integral Equations of the First Kind

The main cause of dynamic errors is the sensors frequency response limitation. One way of solving this problem is designing an effective inverse filter. Since the problem is ill-conditioned, a small uncertainty in the measurement will cause large deviation in reconstructed signals. The amplified noise has to be suppressed at the sacrifice of biasing in estimation. Based on stabilized solutions of Fredholm integral equations of the first kind, the paper presents a group of inverse filters from which correcting dynamic characteristics of measurement systems can be selected or optimized to reduce dynamic errors. Compared with previous work, the method has advantage of generalization. So, it is more flexible in designing inverse filters.

Correction of Signal Distortion Resulting from Measurement Systems Limitation

Abstract: A generalized method for correcting dynamic characteristics of measurement systems is presented to reduce dynamic errors. The cause of dynamic errors is the sensors frequency response limitation. One way of solving this problem is to make use of deconvolution. Since problems are ill-conditioned, a small uncertainty in the measurement will cause large deviation in reconstructed signals. The amplified noise has to be suppressed at the sacrifice of biasing in estimation. In this paper, the problem of dynamic characteristics correction is taken as solving stabilized solutions of Fredholm integral equations. Simulation result shows the validity of the method. A practical application of the method in dynamic calibration and data processing are described.