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 sensor´s 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.