Three-dimensional Shock Wave Overpressure Field Reconstruction Based on Spatial Constrained Joint Dictionary Learning
For the demand of full spatial and temporal reconstruction of shock wave overpressure field under limited measurement point conditions,this paper proposed a 3D shock wave overpressure field reconstruction method based on spatial constraint combined with dictionary learning.Firstly,a 3D walk-time laminar imaging model was established;secondly,the advantage of dictionary learning for image sparse characterization and spa-tial constraint for image edge texture fidelity was utilized;then the alternating minimization idea was used to op-timize the objective function to achieve the high accuracy solution of the large sick sparse matrix;finally,an ex-ternal field test was conducted.The experimental results showed that this method had higher reconstruction ac-curacy compared with the algebraic reconstruction algorithm(ART),joint algebraic reconstruction algorithm(SART),EM algorithm,and the full-region reconstruction error reached 15.81%,which had high application value in the process of spatio-temporal field reconstruction.
three-dimensional reconstructionspace constrainttravel time chromatography
NETL
NSTL
万方数据
维普
