Weak Sparsity Adaptive Matching Pursuit Algorithm based on Environmental Monitoring Sensor Network Data

Due to the undetermined signal sparsity in environmental monitoring applications, the compressed sensing reconstruction algorithm with sparsity adaptive characteristics has better application value. In order to improve the reconstruction accuracy of the reconstruction algorithm, this paper proposes a weak sparsity adaptive matching pursuit algorithm. Firstly, the algorithm constructs the candidate set by weak selection, and then introduces the backtracking idea to filter the candidate set atoms and form a support set. In addition, the algorithm applies the idea of variable step size, and selects different step sizes for different iterations to achieve more accurate and complete reconstruction. Simulation experiments show that the improved algorithm proposed in this paper has higher reconstruction accuracy than similar algorithms.