In order to improve the accuracy and speed of multi-sensor data fusion, a convex combination fusion algorithm and covariance cross fusion algorithm were combined, and the fusion coefficient of the covariance cross fusion algorithm was optimized using the fruit fly optimization algorithm. An improved covariance cross fusion algorithm was proposed, which achieved fast and accurate fusion of multi-sensor data. The simulation results show that the root mean square error of the proposed algorithm for data fusion on the x-axis and y-axis is about 3 m, and the fusion time is about 0.44 s. Compared with data fusion algorithms such as multi Bayesian estimation, fuzzy clustering, and maximum likelihood estimation, it has significant advantages and improves the accuracy and speed of multi-sensor data fusion.