Research of Data Fusion Method of Multi-Sensor Based on Correlation Coefficient of Confidence Distance

ABSTRACT

Because of the sensor or environment problem, the multi-sensor detection data can result in data mutation for the individual sensor. To obtain consistent, stable and accurate tested target description, the paper adopts confidence distance matrix, distance correlation coefficient and p-value significant test to get The number of optimal fusion number of multi-sensor, and uses maximum likelihood estimation to study the multi-sensor data fusion. The results show that the algorithm mentioned by the paper is superior to the multi-sensor consistency data fusion means and is fairly practical.

Keywords:

Confidence distance, correlation coefficient, maximum likelihood estimation, p-value test, support.