In the traditional signal compression perception of reconstruction process, most search for the optimal solution in the solution space is in a probabilistic manner. But when there are multiple local optima in the search space, it is difficult to jump out of the local optima, resulting in poor reconstruction performance. In order to solve the above problems, a new method for compressing and sensing reconstruction of large real-time bandwidth

signals is designed based on the VMD(Variational Mode Decomposition) algorithm. Firstly, the ultra narrow band filtering method is used to process the noise that appears in the real-time bandwidth signals, avoiding distortion in subsequent reconstructed signals. Then, the mayfly algorithm is used to optimize the parameters of the VMD algorithm, by continuously iterating and updating the position and velocity of the mayfly population, gradually approaching the optimal solution, and the optimized parameters are used to improve the accuracy of signal decomposition for large real-time bandwidth. Finally, the real-time bandwidth signal is constructed. Experiment results show that the reconstructed signal has high similarity with the original signal, and the compression efficiency and signal-to-noise ratio performance are excellent. This method can reconstruct real-time bandwidth signals with good reconstruction results.

ultra narrowband filtering, mayfly optimization algorithm, variational mode decomposition(VMD) algorithm, compressive sensing reconstruction method, real time bandwidth signal