Abstract
Pressure sensor output performance susceptible to environmental temperature, voltage fluctuation, etc. parameters of non-target effects, and sensor arrays of sensors exists between the cross-talk, thus greatly reducing the measurement accuracy. In response to these issues the sensor signal processing procedures, the use of multi-sensor information fusion of data from different sensors for effective integration. Mathematical statistics-based approach to the confidence distance matrix and relation matrix of useful data fusion processing, the final maximum probability method and maximum likelihood method for effective integration. The experimental results show that the method eliminates the effects of temperature on the pressure sensors, enabling a single sensor error of the uncertainty of the impact of reduced pressure on the distribution of measurement data to improve the stability and accuracy, making the pressure improved the accuracy of image reconstruction.