Abstract:Considering the characteristics of the data collection and energy constraints in wireless sensor networks, this paper combines clustered routing strategy with compressed sensing data collection method and then proposes a compressive sensing based sampling algorithm with K-Means clustering MST routing. The proposed algorithm uses the sparse projection matrix to reduce the degree of correlation between the projection matrix and sparse matrix, using K-Means clustering MST data fusion tree, reduce the amount of data transmission in the basis to ensure the quality of the data reconstruction. The simulation results show that, this algorithm can improve the network energy efficiency, and also be suitable to all kinds of scale wireless sensor networks.