Research on Data Fusion Method Based on Compressed Sensing

In order to improve the efficiency and fusion effect of data fusion, according to the characteristics of compression sensing theory, this paper proposes a data fusion method based on independent data region division and compression sensing. In the method of this paper, the compressed sensing theory is used to sample the data to obtain the measured values, and the sample data is divided by independent region to form a joint region, then the weight coefficient of mutual information fusion is calculated, and the fused data are obtained according to the compressed sensing coefficient reconstruction method. Simulation results show that compared with the traditional fusion method, this method not only improves the data fusion effect, but also has good stability.