Approaches to accurately data reconstruction for sensor and their performance

Sensors usually have different nonlinearity. This paper proposes two methods for improving sensors´ data reconstruction. The first one is integrated by the least squares and the radical basis function interpolation, which is aimed to the slight nonlinear sensors, and under the limited increament of computation, it can make the results more precise. The second one is used for serious nonlinearity and based on the moving least squares which converts the approximation generally into locally, and the result of this way is also satisfied. By choosing two typical sensors for testing, the efficiency of the two proposed methods were proved.