Research On Spatio-temporal Rconstruction Method Of Shock Wave Overpressure Field Based On Compressive Sensing

The temporal and spatial distribution of shock wave overpressure is the key parameter to measure the damage power of weapon ammunition to target（" hitting hard "）,and is the main basis to analyze the mode of explosion energy conduction and optimize the development of weapon system.With the continuous development of high-power ammunition,the damage area of shock wave continues to increase,and considering the actual situation that the survivability of test nodes is insufficient and the test data after a single explosion is incomplete,it is difficult to guarantee the accuracy of space-time reconstruction of shock wave overpressure field.In view of the above problems,this paper takes full-region spatio-temporal field tomography under incomplete data as the research object,and proposes a shockwave overpressure field reconstruction method based on Total Variation combined with Dictionary Learning by taking advantage of compressed sensing in sparse constraints.Firstly,the performance of empirical mode decomposition（EMD）and variational mode decomposition（VMD）in shock wave signal denoising is compared,and the method of shock wave arrival time extraction based on improved STA/LTA is studied;Secondly,on the basis of traveltime tomography model,TV minimization and dictionary learning are used to regularize the model,and the shockwave overpressure tomography model based on compressive sensing framework is established to improve the reconstruction accuracy and realize the reconstruction of shock wave two-dimensional overpressure field;Thirdly,based on the shock wave overpressure-time relationship,an airborne explosion shock wave overpressure extrapolation model with time and space is established to reconstruct the three-dimensional spatial and temporal distribution of the shock wave overpressure.Finally,simulation validation and field test are carried out to verify the feasibility of the method.By the field test,the reconstruction accuracy of this paper is significantly improved compared with traditional inversion algorithms such as SART,and the average relative error is kept within 10%,which has certain theoretical significance and engineering application value in the fields of weapon and ammunition damage assessment and engineering protection.