Method for balancing accuracy and calculated amount of multifunctional sensor signal reconstruction

Abstract

The invention discloses a method for balancing the accuracy and calculated amount of multifunctional sensor signal reconstruction, which relates to sensors. The method is used for balancing the accuracy and calculated amount of the existing multifunctional sensor signal reconstruction method based on B-spline and extend kalman filtering, and designed for achieving an effect that a balanced signal reconstruction method can ensure the accuracy, and the calculated amount is relatively low. The accuracy and calculated amount of the multifunctional sensor signal reconstruction are quantified by respectively using a minimum mean square error and the number of multiplication operation times; a fitness function is designed by using the two parameters; and the structure of a B-spline is optimized by using a genetic algorithm, so that the fitness function is minimum so as to realize the balancing on the accuracy and calculated amount of the signal reconstruction. According to the invention, the calculated amount required in the process of signal reconstruction can be greatly reduced on the basis of ensuring a high accuracy, and the method disclosed by the invention also can be applied to other multifunctional sensor signal reconstruction methods.

Description

technical field [0001] The invention relates to a sensor, in particular to a method for balancing the reconstruction accuracy and calculation amount of a multifunctional sensor signal. Background technique [0002] Multifunctional sensor is a sensor that can measure multiple physical quantities at the same time, which is one of the main development trends of modern sensing technology. With the development of multifunctional sensors, the corresponding signal reconstruction methods must be studied. At present, although there are many signal reconstruction methods suitable for multifunctional sensors, there are few methods that can guarantee the reconstruction accuracy and can be used on smart chips, and the reconstruction methods based on B-spline and Kalman filter is one of them. However, at present, the selection of the B-spline model structure in this method is generally done manually without corresponding algorithm guidance, so that a large amount of unnecessary calculat...

AI Technical Summary

Problems solved by technology

However, this paper only studies the influence of the optimized parameters on the signal reconstruction error, and does not study its influence on the calculation amount required for parameter identification

Images