Abstract:

The evaporation duct is a kind of electromagnetic wave transmission medium which occurs randomly in the near sea level atmosphere.It is an important part of complex electromagnetic environment in the naval battle field.At present,the method for obtaining the characteristic parameters of the evaporation duct is usually to substitute a variety of marine monitoring data (MMD) into a specific calculation model.These meteorological elements usually include atmospheric temperature,humidity,wind speed,sea surface temperature,etc.In order to obtain the distribution of the evaporation duct in a large area over a long period of time,it is necessary to observe MMD continuously for a long time.Aiming at the problem of poor reconstruction performance of traditional compressed sensing methods in reconstructing time-varying MMD,an online reconstruction method for MMD based on sequential compressed sensing with low-rank regularization is proposed.The algorithm first analyzes the real MMD,revealing the low-rank of the data in the spatial structure,and then constructs the low-rank regularization term combined with the existing historical data with the data fidelity item established according to the condition that the data in the overlapping area at the front and back are equal.Finally the reconstruction optimization algorithm is solved based on the alternating direction multiplier method.Theoretically,the effectiveness of the algorithm is proved by the convergence analysis and complexity analysis,and experimental results verify that the algorithm has a higher reconstruction accuracy.

Key words: sequential compressed sensing, signal reconstruction, low rank, alternating direction multiplier method, marine monitoring data